Q4 2026 MindWalk Holdings Corp Earnings Call

July 22, 2026

Operator: Good afternoon, and welcome to the MindWalk Holdings Corp Financial Results Conference Call for the fiscal year ended 30 April 2026. All participants are in a listen-only mode. Following prepared remarks, we will open the line for questions. This call is being recorded. Before we begin, I would like to remind listeners that today's discussion contains forward-looking statements.

Speaker #1: Good afternoon, and welcome to the Mind Rock Holdings Corp Financial Results Conference Call for the fiscal year ended April 30th, 2026. All participants are in a listen-only mode.

Speaker #1: Following prepared remarks, we will open the line for questions. This call is being recorded. Before we begin, I would like to remind listeners that today's discussion contains forward-looking statements.

Speaker #1: These statements reflect management's current expectations and are subject to risks and uncertainties that could cause actual results to differ materially from those anticipated, including the company's history of net losses, the ability to convert platform adoptions into contracted recurring arrangements, market acceptance of Reef IQ and Lens AI, intellectual property risks, competition, and capital markets conditions.

Operator: These statements reflect management's current expectations and are subject to risks and uncertainties that could cause actual results to differ materially from those anticipated, including the company's history of net losses, the ability to convert platform adoptions into contracted recurring arrangements, market acceptance of ReefIQ and LensAI, intellectual property risks, competition, and capital markets conditions. A fuller description of these risks appears in the company's annual report on Form 20-F and other filings available on SEDAR+ and EDGAR. All financial figures discussed during this call are in Canadian dollars. Financial statements and MD&A are available on the company's website at mindwalkai.com, sec.gov, and on SEDAR+. A replay of this call will also be available following its conclusion. I will now turn the call over to Dr. Jennifer Bath, President and Chief Executive Officer of MindWalk Holdings. Please go ahead, Dr. Bath.

Speaker #1: A fuller description of these risks appears in the company's annual report on Form 20-F and other filings available on Cedar Plus and EDGAR. All financial figures discussed during this call are in Canadian dollars.

Operator: A fuller description of these risks appears in the company's annual report on Form 20-F and other filings available on SEDAR+ and EDGAR. All financial figures discussed during this call are in Canadian dollars. Financial statements and MD&A are available on the company's website at mindwalkai.com, sec.gov, and on SEDAR+. A replay of this call will also be available following its conclusion. I will now turn the call over to Dr. Jennifer Bath, President and Chief Executive Officer of MindWalk Holdings. Please go ahead, Dr. Bath.

Speaker #1: Financial statements and MD&A are available on the company's website at mindwalkai.com, on sec.gov, and on SEDAR+. A replay of this call will also be available following its conclusion.

Speaker #1: I will now turn the call over to Dr. Jennifer Bath, President and Chief Executive Officer of MindWalk Holdings. Please go ahead, Dr. Bath.

Speaker #2: Thank you, and good afternoon, everyone. Fiscal 2026 was a defining year for Mind Rock—the year our discovery engine and the BioNative AI built on top of it came together as a single platform.

Jennifer Bath: Thank you. Good afternoon, everyone. Fiscal 2026 was a defining year for MindWalk, the year our discovery engine and the bio-native AI built on top of it came together as a single platform. That engine has a long record of producing molecules into the clinic. The AI layer makes that biology computable at scale. It was also the year the market's thinking caught up to the thesis that we have held onto from the start, that the durable value in AI for biology is not the model, but the data and the context layer beneath it. A layer that, in our case, rests on 20 years of curated biology no competitor can stand up overnight. Independent research now describes that layer in language that we could not have written better ourselves. This was the year we began to convert that recognition into results.

Speaker #2: That engine has a long record of producing molecules into the clinic. The AI layer makes that biology computable at scale. It was also the year the market's thinking caught up to the thesis that we have held onto from the start.

Speaker #2: The durable value in AI for biology is not the model, but the data and the context layer beneath it—a layer that, in our case, rests on 20 years of curated biology. No competitor can stand up overnight.

Jennifer Bath: A layer that, in our case, rests on 20 years of curated biology no competitor can stand up overnight. Independent research now describes that layer in language that we could not have written better ourselves. This was the year we began to convert that recognition into results.

Speaker #2: Independent research now describes that layer in language that we could not have written better ourselves. This was the year we began to convert that recognition into results.

Speaker #2: We grew revenue by 46%, expanded gross margin to 59%, and narrowed our net loss by more than half—growth and discipline in the same year, not one at the expense of the other.

Jennifer Bath: We grew revenue by 46%, expanded gross margin to 59%, and narrowed our net loss by more than half. Growth and discipline in the same year, not one at the expense of the other. We signed our first two contracted recurring platform agreements, the first recurring platform revenue in the company's history, we launched ReefIQ, which organizes a client's own discovery data into governed biological context. We strengthened the balance sheet through the divestiture of a non-core business, we regained Nasdaq compliance organically, without a reverse split, without dilution, earning inclusion in the Russell 3000E and the Russell Microcap Indexes. The science underwrites all of it. Our discovery work for clients has now put more than 20 molecules into the clinic, that figure reflects only the clients that we are free to name.

Speaker #2: We signed our first two contracted recurring platform agreements. The first recurring platform revenue in the company's history and we launched Reef IQ, which organizes a client's own discovery data into governed biological context.

Speaker #2: We strengthened the balance sheet through the divestiture of a non-core business, and we regained NASDAQ compliance organically—without a reverse split, without dilution. We also earned inclusion in the Russell 3000E and the Russell Microcap indexes.

Jennifer Bath: We strengthened the balance sheet through the divestiture of a non-core business, we regained Nasdaq compliance organically, without a reverse split, without dilution, earning inclusion in the Russell 3000E and the Russell Microcap Indexes. The science underwrites all of it. Our discovery work for clients has now put more than 20 molecules into the clinic, that figure reflects only the clients that we are free to name.

Speaker #2: The science underwrites all of it. Our discovery work for clients has now put more than 20 molecules into the clinic, and that figure reflects only the clients that we are free to name.

Jennifer Bath: Counting the programs that remain confidential, the true number is much more meaningfully higher. Among the clients we can name are Johnson & Johnson's Janssen Vaccines, Sanofi Pasteur, argenx, IDEXX Laboratories, and Xencor. This year, one of those clinical molecules that our work supported became a commercial medicine, approved by the FDA and launched. Those are headlines. Taken together, they mark a very different company than the one that stood here one year ago, they change how the next several years should be underwritten. We've built the record, the market has arrived at the thesis, we've signed the first recurring platform revenue. What's early is scale, that is the opportunity that is in front of us now. For the past several years, the AI drug discovery sector has been consumed by a single question: Whose model will win? That is the wrong question.

Speaker #2: Counting the programs that remain confidential, the true number is much more meaningfully higher. Among the clients we can name are Johnson & Johnson's Janssen Vaccines, Sanofi Pasteur, Argenx, IDEXX Laboratories, and Zencor.

Speaker #2: And this year, one of those clinical molecules that our work supported became a commercial medicine, approved by the FDA and launched. Those are the headlines taken together.

Jennifer Bath: Those are headlines. Taken together, they mark a very different company than the one that stood here one year ago, they change how the next several years should be underwritten. We've built the record, the market has arrived at the thesis, we've signed the first recurring platform revenue. What's early is scale, that is the opportunity that is in front of us now. For the past several years, the AI drug discovery sector has been consumed by a single question: Whose model will win? That is the wrong question.

Speaker #2: They mark a very different company than the one that stood here one year ago, and they change how the next several years should be underwritten.

Speaker #2: We've built the record, the market has arrived at the thesis, and we've signed the first recurring platform revenue. What's early is scale, and that is the opportunity that is in front of us now.

Speaker #2: For the past several years, the AI drug discovery sector has been consumed by a single question: Whose model will win? That is the wrong question.

Speaker #2: And this year, the market has largely moved past it. In its place, a more durable conclusion has taken hold, articulated in strikingly consistent terms across independent research and industry commentary.

Jennifer Bath: This year, the market has largely moved past it. In its place, a more durable conclusion has taken hold, articulated in strikingly consistent terms across independent research and industry commentary. It maps precisely onto the asset MindWalk has built, it comes down to three points. Adoption, not model capability, is the constraint. Proprietary data is the moat, validation is the catalyst. The orchestration layer between AI and biology, the layer the market is now calling the moat, is not something we pivoted into. It's the asset MindWalk has been building for years. HYFT provides the biological representation. ReefIQ organizes a client's own data inside of that representation, preserving provenance and program history across their entire estate. LensAI is where the reasoning happens. Target discovery, candidate diligence, portfolio decision support, and agentic AI workflows that close the loop between in silico prediction and wet lab validation.

Speaker #2: It maps precisely onto the asset Mind Rock has built, and it comes down to three points. Adoption, not model capability, is the constraint. Proprietary data is the moat, and validation is the catalyst.

Speaker #2: The orchestration layer between AI and biology—the layer the market is now calling the moat—is not something we pivoted into. It's the asset Mind Rock has been building for years.

Jennifer Bath: The orchestration layer between AI and biology, the layer the market is now calling the moat, is not something we pivoted into. It's the asset MindWalk has been building for years. HYFT provides the biological representation. ReefIQ organizes a client's own data inside of that representation, preserving provenance and program history across their entire estate.

Speaker #2: HIFT provides the biological representation. Reef IQ organizes a client's own data inside that representation, preserving provenance and program history across their entire estate.

Speaker #2: And Lens AI is where the reasoning happens: target discovery, candidate diligence, portfolio decision support, and agentic AI workflows that close the loop between in silico prediction and wet lab validation.

Jennifer Bath: LensAI is where the reasoning happens. Target discovery, candidate diligence, portfolio decision support, and agentic AI workflows that close the loop between in silico prediction and wet lab validation.

Jennifer Bath: The long-term advantage is not the model. Models are replicable. It's HYFT. It's 20 years of curated, function annotated biology encoding the sequence and the structure and the functional relationships that let any model reason over biology with context, the context that it otherwise lacks. That foundation took two decades to build, it cannot be stood up overnight. For each client, the value compounds in their own governed environment. Every program they run inside of ReefIQ makes their context richer and their work faster, with their data remaining theirs. This is where the thesis begins translating into commercial execution. There's a validation ladder in this business, the rungs behind us and ahead of us are worth us being really clear about here. The first rung is the application layer adoption. Clients engaging LensAI to solve a defined workflow problem on a contracted recurring basis.

Speaker #2: The long-term advantage is not the model. Models are replicable. It's HIFT. It's 20 years of curated, function-annotated biology, encoding the sequence and the structure and the functional relationships that let any model reason over biology with the context that it otherwise lacks.

Speaker #2: That foundation took two decades to build, and it cannot be stood up overnight. For each client, the value compounds in their own governed environment.

Speaker #2: Every program they run inside of Reef IQ makes their context richer, and their work faster. With their data remaining there, this is where the thesis begins translating into commercial execution.

Jennifer Bath: Every program they run inside of ReefIQ makes their context richer and their work faster, with their data remaining theirs. This is where the thesis begins translating into commercial execution. There's a validation ladder in this business, the rungs behind us and ahead of us are worth us being really clear about here. The first rung is the application layer adoption. Clients engaging LensAI to solve a defined workflow problem on a contracted recurring basis.

Speaker #2: There's a validation ladder in this business, and the wrongs behind us, and ahead of us, are worth us being really clear about here. The first wrong is the application layer adoption.

Speaker #2: Clients are engaging Lens AI to solve a defined workflow problem on a contracted recurring basis. In the second half of fiscal year 2026, we signed our first enterprise-layer SaaS agreement.

Jennifer Bath: In the H2 of fiscal year 2026, we signed our first enterprise layer SaaS agreement, then a second contract in Q4. Together, they mark the first recurring platform revenue in this company's history. That's the entry point. A client trusts the platform with a discrete application. They see the result, and it builds conviction from there. The next rung matters more. It's clients engaging ReefIQ to organize and manage their data across their broader estate. Well-organized, context-rich data is where their competitive edge comes from. At the Jones Trading AI Day fireside chat last month, when asked, I accordingly told institutional investors that this is the validation to watch for from MindWalk. The commercial engine we're building runs alongside that ladder from application layer adoption toward the deeper data management relationships above it.

Speaker #2: And then a second contract in the fourth quarter. Together, they mark the first recurring platform revenue in this company's history. That's the entry point.

Speaker #2: A client trusts the platform with a discreet application. They see the result, and it builds conviction from there. The next round matters more. It's clients engaging Reef IQ to organize and manage their data across their broader estate.

Jennifer Bath: The next rung matters more. It's clients engaging ReefIQ to organize and manage their data across their broader estate. Well-organized, context-rich data is where their competitive edge comes from. At the Jones Trading AI Day fireside chat last month, when asked, I accordingly told institutional investors that this is the validation to watch for from MindWalk. The commercial engine we're building runs alongside that ladder from application layer adoption toward the deeper data management relationships above it.

Speaker #2: Well-organized, context-rich data is where their competitive edge comes from. And at the Jones Trading AI Day fireside chat last month, when asked, I accordingly told institutional investors that this is the validation to watch for from Mind Rock.

Speaker #2: The commercial engine we're building runs alongside that ladder from application layer adoption toward the deeper data management relationships above it. The most rigorous validation of a discovery capability is the medicines that reach the patients because of it.

Jennifer Bath: The most rigorous validation of a discovery capability is the medicines that reach the patients because of it. Behind that record of dozens of molecules that we have assisted with in producing for the clinic, 10 are in active phase I through phase III trials, four are first-in-class, and that work is backed by more than 400 peer-reviewed publications, and issued patents. These are client-owned assets. The value of each molecule accrues to the company whose name is on it. What accrues to MindWalk is a foundation. A track record of molecules reaching the clinic is what earns a discovery company the standing to build on it. Deeper partnerships, co-development, milestones, and royalty participation, and the recurring revenue that comes from being embedded in how a program advances. The clinical record is the proof.

Speaker #2: Behind that record of dozens of molecules that we have assisted with in producing for the clinic, 10 are in active phase one through phase three trials.

Speaker #2: Four are first-in-class. And that work is backed by more than 400 peer-reviewed publications and issued patents. These are client-owned assets. The value of each molecule accrues to the company whose name is on it.

Jennifer Bath: The value of each molecule accrues to the company whose name is on it. What accrues to MindWalk is a foundation. A track record of molecules reaching the clinic is what earns a discovery company the standing to build on it. Deeper partnerships, co-development, milestones, and royalty participation, and the recurring revenue that comes from being embedded in how a program advances. The clinical record is the proof.

Speaker #2: What accrues to Mind Rock is a foundation—a track record of molecules reaching the clinic. That is what earns a discovery company the standing to build on it.

Speaker #2: Deeper partnerships, co-development, milestones, and royalty participation—and the recurring revenue that comes from being embedded in how a program advances. The clinical record is the proof; the partnerships and the recurring revenue built on top of it are where that value starts to compound.

Jennifer Bath: The partnerships and the recurring revenue built on top of it are where that value starts to compound. In June 2026, one of those programs reached patients. A therapeutic our client developed for a rare, debilitating autoimmune disease was approved by the FDA and launched commercially. MindWalk's role wasn't the molecule itself. It was specialized. The anti-idiotypic reagents our client used to build and to validate the bioanalytical assays that their molecule had to clear on its way through clinical development, including in response to a direct request from the agency. That's a contribution that we're proud of because it points to something that I believe the market overlooks. Getting a molecule to patients takes far more than designing something that binds.

Speaker #2: In June 2026, one of those programs reached patients: a therapeutic our client developed for a rare, debilitating autoimmune disease was approved by the FDA and launched commercially.

Speaker #2: Mind Rock's role wasn't the molecule itself. It was specialized—the anti-idiotypic reagents our client used to build and to validate the bioanalytical assays that their molecule had to clear on its way through clinical development, including in response to a direct request from the agency.

Jennifer Bath: The anti-idiotypic reagents our client used to build and to validate the bioanalytical assays that their molecule had to clear on its way through clinical development, including in response to a direct request from the agency. That's a contribution that we're proud of because it points to something that I believe the market overlooks. Getting a molecule to patients takes far more than designing something that binds.

Speaker #2: And that's a contribution that we're proud of, because it points to something that I believe the market overlooks. Getting a molecule to patients takes far more than designing something that binds.

Speaker #2: It takes the specialized tools that measure a drug, that validate the assays that are behind it, and stand up to the regulatory rigor that an approval demands.

Jennifer Bath: It takes the specialized tools that measure a drug, that validate the assays that are behind it and stand up to the regulatory rigor that an approval demands. Most of the field is so focused on that first step, on discovering a molecule. We support molecules across the path to approval, and that breadth is far harder to replicate than a single binder. It's also how a discovery relationship becomes a deeper one, the kind of collaboration that compounds into partnership and recurring work. The track record is more than credibility. It's two decades of learning what it takes to move a molecule from discovery all the way through approval. Now, built into LensAI and being applied to our own programs for the first time. Our dengue program has produced strong preclinical results, a conserved pan-serotype target identified computationally and then validated in vivo across two independent campaigns.

Speaker #2: Most of the field is so focused on that first step—on discovering a molecule. We support molecules across the path to approval, and that breadth is far harder to replicate than a single binder.

Speaker #2: It's also how a discovery relationship becomes a deeper one—the kind of collaboration that compounds into partnership and recurring work. The track record is more than credibility.

Jennifer Bath: The track record is more than credibility. It's two decades of learning what it takes to move a molecule from discovery all the way through approval. Now, built into LensAI and being applied to our own programs for the first time. Our dengue program has produced strong preclinical results, a conserved pan-serotype target identified computationally and then validated in vivo across two independent campaigns.

Speaker #2: It's two decades of learning what it takes to move a molecule from discovery all the way through approval, now built into Lens AI, and being applied to our own programs for the first time.

Speaker #2: Our dengue program has produced strong preclinical results. A conserved pan-serotype target was identified computationally, and then validated in vivo across two independent campaigns. The science speaks to exactly what the platform was built to do.

Jennifer Bath: The science speaks to exactly what the platform was built to do. GLP-1 shows the same engine pointed at a different problem. We designed the receptor agonist sequence in silico, then we tested it in vitro, where they activated GLP-1 receptor comparable or superior to semaglutide, one of the most competitive targets in medicine. It is early, and of course, we will update you as it matures, but early results on a target that hard are worth paying attention to. Influenza extends the pattern. Across more than 2,000 strains of influenza, HYFT found a functional invariant that holds where the sequence itself keeps changing. With conventional alignment, it simply cannot see. Behind those are more.

Speaker #2: GLP-1 shows the same engine pointed at a different problem. We designed the receptor agonist sequence in silico, and then we tested it in vitro.

Speaker #2: Where they activated, the GLP-1 receptor was comparable or superior to semaglutide. This is one of the most competitive targets in medicine. It's early, and of course, we will update you as it matures.

Jennifer Bath: It is early, and of course, we will update you as it matures, but early results on a target that hard are worth paying attention to. Influenza extends the pattern. Across more than 2,000 strains of influenza, HYFT found a functional invariant that holds where the sequence itself keeps changing. With conventional alignment, it simply cannot see. Behind those are more.

Speaker #2: But early results on a target that hard are worth paying attention to. Influenza extends the pattern across more than 2,000 strains of influenza. HIPT found a functional invariant that holds where the sequence itself keeps changing.

Speaker #2: That kind of target-convention alignment simply is—that can with conventional alignment—it simply cannot see. Behind those are more pandemic response platforms deployed this year against Ebola and hantavirus, and a broader set of infectious disease and autoimmune programs that we’ll bring forward as they earn it.

Jennifer Bath: Our pandemic response platform deployed this year against Ebola and Hantavirus, and a broader set of infectious disease and autoimmune programs that we will bring forward as they earn it. On 1 July 2026, we filed a patent application extending our foundational HYFT patent, protecting our architecture behind how biological context is organized and made computable in our system. The context layer is where the long-term value in biological AI accrues, and this patent is built to protect that. Fiscal year 2026 also marked an important milestone in restoring institutional credibility. We regained Nasdaq compliance organically without a reverse split or other dilutive measures, reflecting genuine improvement in market support and investor confidence. Effective after US market close on 26 June 2026, MindWalk was added to the Russell 3000E Index and the Russell Microcap Index.

Speaker #2: On July 1, 2026, we filed a patent application extending our foundational HIPT patent, protecting our architecture behind how biological context is organized and made computable in our system.

Speaker #2: The context layer is where the long-term value in biological AI accrues, and this patent is built to protect that. Fiscal year 2026 also marked an important milestone in restoring institutional credibility.

Jennifer Bath: The context layer is where the long-term value in biological AI accrues, and this patent is built to protect that. Fiscal year 2026 also marked an important milestone in restoring institutional credibility. We regained Nasdaq compliance organically without a reverse split or other dilutive measures, reflecting genuine improvement in market support and investor confidence. Effective after US market close on 26 June 2026, MindWalk was added to the Russell 3000E Index and the Russell Microcap Index.

Speaker #2: We regained NASDAQ compliance organically, without a reverse split or other dilutive measures, reflecting genuine improvement in market support and investor confidence. Effective after the U.S. market close on June 26, 2026, Mind Rock was added to the Russell 3000E Index and the Russell Microcap Index.

Speaker #2: Russell inclusion expands institutional visibility, increases eligibility for index ownership, and represents another important milestone in Mind Rock's continued evolution as a publicly traded company.

Jennifer Bath: Russell inclusion expands institutional visibility, increases eligibility for index ownership, and represents another important milestone in MindWalk's continued evolution as a publicly traded company. We completed the transition from ImmunoPrecise Antibodies to MindWalk Holdings Corp in September 2025, creating one unified commercial platform that simplifies how the company goes to market and supports more efficient growth. Nine months in, the metrics are consistent and directional. AI citations of our content have more than doubled above the legacy brand. The number of referring domains to our digital presence are up materially. Organic keyword coverage has expanded. Sustained daily dollar volume is a multiple of the pre-branded median. Analyst coverage has expanded. These metrics all reflect a company being found by the audience that it is now serving. In October, Scott Areglado joined as chief financial officer, bringing the finance and capital markets discipline that you will hear from him shortly.

Speaker #2: We completed the transition from ImmunoPrecise Antibodies to Mind Rock Holdings Corp in September 2025, creating one unified commercial platform that simplifies how the company goes to market and supports more efficient growth.

Jennifer Bath: Nine months in, the metrics are consistent and directional. AI citations of our content have more than doubled above the legacy brand. The number of referring domains to our digital presence are up materially. Organic keyword coverage has expanded. Sustained daily dollar volume is a multiple of the pre-branded median.

Speaker #2: Nine months in, the metrics are consistent and directional. AI citations of our content have more than doubled compared to the legacy brand. The number of referring domains to our digital presence is up materially.

Speaker #2: Organic keyword coverage has expanded. The sustained daily dollar volume is a multiple of the pre-branded median. Analyst coverage has also expanded. These metrics all reflect a company being found by the audience that it is now serving.

Jennifer Bath: Analyst coverage has expanded. These metrics all reflect a company being found by the audience that it is now serving. In October, Scott Areglado joined as chief financial officer, bringing the finance and capital markets discipline that you will hear from him shortly.

Speaker #2: In October, Scott Araglado joined as Chief Financial Officer, bringing the finance and capital markets discipline that you'll hear from him shortly. On the commercial side, we deepened our enterprise business development team this year, and we've added two more senior professionals in both Boston and San Francisco to drive platform adoption in the two largest US biopharma markets.

Jennifer Bath: On the commercial side, we deepened our enterprise business development team this year, and we have added two more senior professionals in both Boston and San Francisco to drive platform adoption in the two largest US biopharma markets. In the first part of the fiscal year, we completed the sale of our Netherlands wet lab operations to AVS Bio, strengthening the balance sheet. Scott will cover the financial impact of that. More importantly, it sharpened our focus on a genuine structural advantage. At MindWalk, computation and wet lab operate as one integrated system, not two functions handing work back and forth. That integration is why our programs compound data and biological context at a rate that conventional discovery cannot match. Starting today, we are in San Francisco at AMD Advancing AI 2026, AMD's flagship event. A company AMD chose to build with. That choice is the signal.

Speaker #2: In the first part of the fiscal year, we completed the sale of our Netherlands wet lab operations to AVS Bio, strengthening the balance sheet.

Speaker #2: Scott will cover the financial impact of that. More importantly, it sharpened our focus on a genuine structural advantage. At Mind Rock, computation and wet lab operate as one integrated system, not two functions handing work back and forth.

Jennifer Bath: More importantly, it sharpened our focus on a genuine structural advantage. At MindWalk, computation and wet lab operate as one integrated system, not two functions handing work back and forth. That integration is why our programs compound data and biological context at a rate that conventional discovery cannot match. Starting today, we are in San Francisco at AMD Advancing AI 2026, AMD's flagship event. A company AMD chose to build with. That choice is the signal.

Speaker #2: That integration is why our programs compound data and biological context at a rate that conventional discovery cannot match. Starting today, we are in San Francisco at AMD, advancing AI 2026.

Speaker #2: AMD's flagship event, a company AMD chose to build with. That choice is the signal. AMD is one of the largest companies in the world, and it does not put its engineering weight behind marketing relationships.

Jennifer Bath: AMD is one of the largest companies in the world. It does not put its engineering weight behind marketing relationships. It co-designs with a small number of companies whose work is demanding enough to push its hardware. It selected MindWalk. This is an engineering partnership. AMD's teams work alongside ours to optimize the infrastructure our AI platform runs on. Migrating our libraries off of a CUDA lock stack onto AMD's Open ROCm stack was a joint build. Production infrastructure that runs every single day at MindWalk. AMD's published case study puts the results in hard numbers. On Instinct MI300X hardware, we screened roughly 170,000 antibody pairs in about four and a half hours, work that had taken 145 days previously. Cost per million samples in literature mining fell about 39%, and embedding throughput rose about 70%.

Speaker #2: It co-designs with a small number of companies whose work is demanding enough to push its hardware, and it has selected Mind Rock. This is an engineering partnership.

Speaker #2: AMD's teams work alongside ours to optimize the infrastructure our AI platform runs on. Migrating our libraries off of a CUDA lock stack onto AMD's open ROCm stack was a joint build.

Jennifer Bath: Migrating our libraries off of a CUDA lock stack onto AMD's Open ROCm stack was a joint build. Production infrastructure that runs every single day at MindWalk. AMD's published case study puts the results in hard numbers. On Instinct MI300X hardware, we screened roughly 170,000 antibody pairs in about four and a half hours, work that had taken 145 days previously. Cost per million samples in literature mining fell about 39%, and embedding throughput rose about 70%.

Speaker #2: Production infrastructure that runs every single day at Mind Walk. AMD's published case study puts the results in hard numbers. On Instinct MI300X hardware, we screened roughly 170,000 antibody pairs in about four and a half hours.

Speaker #2: Work that had taken 145 days previously. Cost per million samples in literature mining fell about 39%, and embedding throughput rose about 70%. Speaking alongside us at Jones Trading AI Day fireside in June, AMD described being highly selective about who it co-designs with and pointed to Mind Rock as having the capabilities the market is looking for.

R. Scott Areglado: Thank you, Jennifer. Good afternoon, everyone. I will take you through the fiscal 2026 financial results and the drivers behind them. As a reminder, all figures are in Canadian dollars unless otherwise specified and are preliminary pending the filing of our annual report on Form 20-F. The financial story of fiscal 2026 is straightforward. Revenue growth, margin expansion, disciplined operating investment in the commercial engine, and a stronger balance sheet. Revenue grew meaningfully year over year from CAD 10.6 million to CAD 15.6 million, or a 46% increase in fiscal year 2026. Revenue for Q4 2026 was CAD 4.1 million, or a 50% increase as compared to CAD 2.7 million for Q4 2025. The quality dimension of that revenue is as important as the volume. This was the year we booked the first contracted recurring platform revenue in MindWalk's history through the two enterprise LensAI agreements Jennifer described.

Speaker #2: On the record, in front of institutional investors. There is more from all of this, and our interactions at this conference, that we expect to share shortly.

Speaker #2: Let me turn this call over now to Scott to review our financial results, and then I'll make some closing comments before Q&A. Scott.

Speaker #1: Thank you, Jennifer, and good afternoon, everyone. I will take you through the fiscal 2026 financial results and the drivers behind them. As a reminder, all figures are in Canadian dollars unless otherwise specified and are preliminary, pending the filing of our annual report on Form 20-F.

Jennifer Bath: Thank you, Jennifer, and good afternoon, everyone. I will take you through the fiscal 2026 financial results and the drivers behind them. As a reminder, all figures are in Canadian dollars unless otherwise specified and are preliminary pending the filing of our annual report on Form 20-F. The financial story of fiscal 2026 is straightforward. Revenue growth, margin expansion, disciplined operating investment in the commercial engine, and a stronger balance sheet. Revenue grew meaningfully year over year from 10.6 million to 15.6 million, or a 46% increase in fiscal year 2026. Revenue for Q4 2026 was 4.1 million, or a 50% increase as compared to 2.7 million for Q4 2025. The quality dimension of that revenue is as important as the volume. This was the year we booked the first contracted recurring platform revenue in MindWalk's history through the two enterprise LensAI agreements Jennifer described.

Speaker #1: The financial story of fiscal 2026 is straightforward: revenue growth, margin expansion, disciplined operating investment in the commercial engine, and a stronger balance sheet. Revenue grew meaningfully year over year, from $10.6 million to $15.6 million, or a 46% increase in fiscal year 2026.

Jennifer Bath: Revenue growth, margin expansion, disciplined operating investment in the commercial engine, and a stronger balance sheet. Revenue grew meaningfully year over year from 10.6 million to 15.6 million, or a 46% increase in fiscal year 2026. Revenue for Q4 2026 was 4.1 million, or a 50% increase as compared to 2.7 million for Q4 2025.

Speaker #1: Revenue for Q4 2026 was $4.1 million, representing a 50% increase compared to $2.7 million for Q4 2025. The quality dimension of that revenue is as important as the volume.

Jennifer Bath: The quality dimension of that revenue is as important as the volume. This was the year we booked the first contracted recurring platform revenue in MindWalk's history through the two enterprise LensAI agreements Jennifer described.

Speaker #1: This was the year we booked the first contracted, recurring platform revenue in Mind Rock’s history through the two enterprise Lens AI agreements Jennifer described.

Speaker #1: Those are software layer engagements, carrying different economics than project-based services, and they open a revenue model we intend to scale. Gross margin expanded from $5.7 million, or 54% of revenue, to $9.1 million, or 59% of revenue.

R. Scott Areglado: Those are software layer engagements carrying different economics than project-based services. They open a revenue model we intend to scale. Gross margin expanded from CAD 5.7 million or 54% of revenue to CAD 9.1 million or 59% of revenue. Gross margin for Q4 2026 was CAD 2.5 million or 61%, compared to CAD 1.6 million or 58%. This reflects a shift in revenue mix toward platform and higher margin service work, together with structural efficiencies following the divestiture. Now on to operating expenses. Total operating expenses were CAD 24.1 million, as compared to CAD 42.6 million in the prior year. However, the prior year included CAD 21.2 million of intangible asset amortization and CAD 1.5 million of impairment that did not recur. On a comparable basis, operating expenses increased by approximately CAD 4.2 million, which reflects deliberate investments in the commercial infrastructure.

Speaker #1: Gross margin for Q4 2026 was $2.5 million, or 61%, compared to $1.6 million, or 58%. This reflects a shift in revenue mix toward platform and higher-margin service work, together with structural efficiencies following the divestiture.

Speaker #1: Now, onto operating expenses. Total operating expenses were $24.1 million, as compared to $42.6 million in the prior year. However, the prior year included $21.2 million of intangible asset amortization and $1.5 million of impairment that did not recur.

R. Scott Areglado: Now on to operating expenses. Total operating expenses were CAD 24.1 million, as compared to CAD 42.6 million in the prior year. However, the prior year included CAD 21.2 million of intangible asset amortization and CAD 1.5 million of impairment that did not recur. On a comparable basis, operating expenses increased by approximately CAD 4.2 million, which reflects deliberate investments in the commercial infrastructure.

Speaker #1: On a comparable basis, operating expenses increased by approximately $4.2 million, which reflects deliberate investments in the commercial infrastructure. Research and development expense for fiscal year 2026 was $4.9 million, up slightly from $4.2 million, demonstrating continued investment in our commercial infrastructure.

R. Scott Areglado: Research and development expense for fiscal year 2026 was CAD 4.9 million, up slightly from CAD 4.2 million, demonstrating continuing investment in our commercial infrastructure. Research and development expense for Q4 2026 was CAD 1.6 million, as compared to CAD 0.8 million in Q4 2025. Sales and marketing expense were CAD 5.9 million in fiscal year 2026, up from CAD 3.6 million for the same period in 2025, reflecting increased staffing and expanded North American business development capacity. Sales and marketing expenses for Q4 2026 were CAD 1.5 million versus CAD 0.9 million in Q4 2025. We expect operating expenses to increase as we continue to invest in our pipeline assets and ReefIQ. Net loss from continuing operations was CAD 15.1 million in 2026 versus CAD 33.1 million in the prior year. Net loss for the fiscal year 2026 was approximately CAD 14 million as compared to CAD 30.2 million in the prior year.

Speaker #1: Research and development expense for Q4 2026 was $1.6 million, as compared to $0.8 million in Q4 2025. Sales and marketing expense was $5.9 million in fiscal year 2026, up from $3.6 million for the same period in 2025.

Speaker #1: Reflecting increased staffing and expanded North American business development capacity. Sales and marketing expenses for Q4 2026 were $1.5 million versus $0.9 million in Q4 2025.

R. Scott Areglado: Sales and marketing expenses for Q4 2026 were CAD 1.5 million versus CAD 0.9 million in Q4 2025. We expect operating expenses to increase as we continue to invest in our pipeline assets and ReefIQ. Net loss from continuing operations was CAD 15.1 million in 2026 versus CAD 33.1 million in the prior year. Net loss for the fiscal year 2026 was approximately CAD 14 million as compared to CAD 30.2 million in the prior year.

Speaker #1: We expect operating expenses to increase as we continue to invest in our pipeline assets and Reef IQ. Net loss from continuing operations was $15.1 million in 2026 versus $33.1 million in the prior year.

Speaker #1: Net loss for the fiscal year 2026 was approximately $14 million, as compared to $30.2 million in the prior year. Loss per share from continuing operations was $0.33 per share versus $0.99 in the prior year.

R. Scott Areglado: Loss per share from continuing operations was CAD 0.33 per share versus CAD 0.99 in the prior year. For the quarter ended Q4 2026, net loss from continuing operations was CAD 3.9 million versus CAD 3.4 million in the prior year quarter. Net loss for Q4 2026 was CAD 3.9 million as compared to CAD 2.2 million in the prior year. Now turning to the balance sheet. We ended the year with a cash balance of CAD 11.5 million as of 30 April 2026, as compared to CAD 10.8 million as of 30 April 2025. In summary, the company generated non-dilutive capital by divesting our European operations for net proceeds of USD 10.3 million without sacrificing revenue growth. We continue to invest in the infrastructure that matters. Integrating ReefIQ into our lab operations and advancing our engineering work with AMD, the foundation beneath both our own pipeline and our clients' data management.

Speaker #1: For the quarter ended Q4 2026, net loss from continuing operations was $3.9 million versus $3.4 million in the prior year quarter. Net loss for the fourth quarter of 2026 was $3.9 million as compared to $2.2 million in the prior year.

Speaker #1: Now turning to the balance sheet. We ended the year with a cash balance of $11.5 million as of April 30, 2026, compared to $10.8 million as of April 30, 2025.

R. Scott Areglado: Now turning to the balance sheet. We ended the year with a cash balance of CAD 11.5 million as of 30 April 2026, as compared to CAD 10.8 million as of 30 April 2025. In summary, the company generated non-dilutive capital by divesting our European operations for net proceeds of USD 10.3 million without sacrificing revenue growth.

Speaker #1: In summary, the company generated non-dilutive capital by divesting our European operations for net proceeds of $10.3 million, without sacrificing revenue growth. We continue to invest in the infrastructure that matters.

R. Scott Areglado: We continue to invest in the infrastructure that matters. Integrating ReefIQ into our lab operations and advancing our engineering work with AMD, the foundation beneath both our own pipeline and our clients' data management. With that, I will turn the call back to Jennifer. Jennifer?

Speaker #1: Integrating Reef IQ into our lab operations and advancing our engineering work with AMD. This serves as the foundation beneath both our own pipeline and our clients' data management.

Speaker #1: With that, I will turn the call back to Jennifer. Jennifer.

R. Scott Areglado: With that, I will turn the call back to Jennifer. Jennifer?

Speaker #2: Thank you, Scott. As we enter fiscal year 2027, our strategy coalesces around three pillars—the same three we've communicated in our filings, and the same three by which we would ask you to measure us.

Jennifer Bath: Thank you, Scott. As we enter fiscal year 2027, our strategy coalesces around three pillars, the same three we've communicated in our filings and the same three by which we would ask you to measure us. Pillar one, build intelligence-driven recurring revenue. In fiscal year 2026, we integrated LensAI into every new client program, and clients began paying to add LensAI applications to their work. The first application layer revenue at scale. That adoption is deepening. Double-digit clients are now in the LensAI portal, accessing their data directly, with dozens more of programs actively moving into that usage. This is our lab in a loop, outputs from our laboratory work that flow back through the portal where ReefIQ enriches each client's context with every run. It's the feeder into what comes next, broader data management adoption and recurring SaaS licensing.

Speaker #2: Pillar one: build intelligence-driven recurring revenue. In fiscal year 2026, we integrated Lens AI into every new client program, and clients began paying to add Lens AI applications to their work.

Speaker #2: The first application layer revenue at scale. That adoption is deepening—double-digit clients are now in the Lens AI portal, accessing their data directly, with dozens more programs actively moving into that usage.

Jennifer Bath: The first application layer revenue at scale. That adoption is deepening. Double-digit clients are now in the LensAI portal, accessing their data directly, with dozens more of programs actively moving into that usage. This is our lab in a loop, outputs from our laboratory work that flow back through the portal where ReefIQ enriches each client's context with every run. It's the feeder into what comes next, broader data management adoption and recurring SaaS licensing.

Speaker #2: This is our lab-in-a-loop: outputs from our laboratory work flow back through the portal, where Reef IQ enriches each client's context with every run.

Speaker #2: And it's the feeder into what comes next—broader data management adoption and recurring SaaS licensing. That deepening is the leading indicator of the recurring revenue engine that we're building.

Jennifer Bath: That deepening is the leading indicator of the recurring revenue engine that we're building. The market is telling us engagement by engagement that this is the layer it needs. Pillar 2, advance and protect the internal asset portfolio. We are building a proprietary biologics and vaccine pipeline, dengue, influenza, GLP-1, and our pandemic response platform work, and additional programs across infectious disease and autoimmunity that we will disclose as they mature. These are not service arrangements. They are assets we own, built into our own platform. Our wet lab is one of the most productive antibody discovery engines in the industry. It has put dozens of molecules into the clinic for our clients, and it is doing that work right now. That is the discovery capability behind this pipeline. What's new is the level 2 we've added to it. Our AI.

Speaker #2: The market is telling us, engagement by engagement, that this is the layer it needs. Pillar Two: advance and protect the internal asset portfolio. We are building a proprietary biologics and vaccine pipeline.

Speaker #2: Dengue, influenza, GLP-1, and our pandemic response platform work, and additional programs across infectious disease and autoimmunity—these we will disclose as they mature. These are not service arrangements.

Jennifer Bath: These are not service arrangements. They are assets we own, built into our own platform. Our wet lab is one of the most productive antibody discovery engines in the industry. It has put dozens of molecules into the clinic for our clients, and it is doing that work right now. That is the discovery capability behind this pipeline. What's new is the level 2 we've added to it. Our AI.

Speaker #2: They are assets we own, built into our own platform. Our wet lab is one of the most productive antibody discovery engines in the industry.

Speaker #2: It has put dozens of molecules into the clinic for our clients, and it is doing that work right now. That is the discovery capability behind this pipeline.

Speaker #2: What's new is the second level we've added to it. Our AI, HIFT, encodes the relationships between the sequence, the structure, and the function.

Jennifer Bath: It encodes the relationships between the sequence, the structure, and the function. Our models reason with biological context that others don't. Surfacing targets and designing molecules that conventional approaches never surface because they can't see that connection. Neither capability is borrowed, and neither is new to us. Now they run as one engine. The AI points to the lab at the right experiments, and the lab's results deepen the AI and every program compounds richer in context than either could reach alone. Pillar 3, deepen enterprise partnerships. The relationships that matter are the ones that change how the work goes or how the work gets done. AMD is the proof. Joint engineering that made our platform faster, made our platform more scalable, running in production every single day, not a logo on a slide. We're building the same kind of relationship with pharmaceutical and biotech companies right now.

Speaker #2: So, our models reason with biological context that others don't—surfacing targets and designing molecules that conventional approaches never surface, because they can't see that connection.

Speaker #2: Neither capability is borrowed, and neither is new to us. Now they run as one engine. The AI points the lab to the right experiments, and the lab's results deepen the AI, and every program compounds richer in context than either could reach alone.

Jennifer Bath: The AI points to the lab at the right experiments, and the lab's results deepen the AI and every program compounds richer in context than either could reach alone. Pillar 3, deepen enterprise partnerships. The relationships that matter are the ones that change how the work goes or how the work gets done.

Speaker #2: Pillar three: deepen enterprise partnerships. The relationships that matter are the ones that change how the work goes or how the work gets done. AMD is the proof—joint engineering that made our platform faster, made our platform more scalable, running in production every single day.

Jennifer Bath: AMD is the proof. Joint engineering that made our platform faster, made our platform more scalable, running in production every single day, not a logo on a slide. We're building the same kind of relationship with pharmaceutical and biotech companies right now.

Speaker #2: Not a logo on a slide. We're building the same kind of relationship with pharmaceutical and biotech companies right now. In those relationships, embedded in the artificial intelligence and embedded on the capabilities running with MindWalk and AMD in combination.

Jennifer Bath: In those relationships, embedded in the artificial intelligence and embedded on the capabilities, running with MindWalk and AMD in combination. When those are far enough along to show results, that's when we'll announce them, and with that evidence, not just the name. The AI drug discovery sector is being repriced right now away from the model toward the context layer beneath it. That is the layer we have spent 2 decades building, and it is the layer that we lead. This is no longer our view alone. Independent research has arrived at it. Our clients are arriving at it, one expanded engagement, one platform agreement, one medicine reaching patients at a time. Fiscal year 2026 was the year that the market caught up to what we built.

Speaker #2: When those are far enough along to show results, that's when we'll announce them—and with that, evidence, not just the name. The AI drug discovery sector is being repriced right now, away from the model toward the context layer beneath it.

Jennifer Bath: The AI drug discovery sector is being repriced right now away from the model toward the context layer beneath it. That is the layer we have spent 2 decades building, and it is the layer that we lead. This is no longer our view alone. Independent research has arrived at it. Our clients are arriving at it, one expanded engagement, one platform agreement, one medicine reaching patients at a time. Fiscal year 2026 was the year that the market caught up to what we built.

Speaker #2: That is the layer we have spent two decades building, and it is the layer that we lead. This is no longer our view alone.

Speaker #2: Independent research has arrived at it. Our clients are arriving at it. One expanded engagement, one platform agreement, one medicine reaching patients at a time.

Speaker #2: Fiscal year 2026 was the year that the market caught up to what we built. Fiscal year 2027 is the year that we press the advantage.

Jennifer Bath: Fiscal year 2027 is the year that we press the advantage while we are in front, while the field is still catching up, and while the assets we own are compounding on a foundation that no one else has. This week, we are on that stage at AMD Advancing AI in front of the entire industry. It's a fitting place to be because the company we're describing today is the one the market is now looking for. We thank our shareholders, our clients, and our team for their confidence. Operator, please open the line for questions.

Speaker #2: While we are in front, while the field is still catching up, and while the assets we own are compounding on a foundation that no one else has.

Speaker #2: This week, we are on that stage at AMD, advancing AI in front of the entire industry. It's a fitting place to be, because the company we're describing today is the one the market is now looking for.

Speaker #2: We thank our shareholders, our clients, and our team for their confidence. Operator, please open the line for questions.

Speaker #3: Thank you. And everyone, if you would like to ask a question, please press star one on your telephone keypad. Once again, that is star one if you have a question.

Operator: Thank you. Everyone, if you would like to ask a question, please press star one on your telephone keypad. Once again, that is star one if you have a question. Our first question comes from Swayam Ramakanth from H.C. Wainwright.

Speaker #3: Our first question comes from Soyampakula Ramanka from HC Wainwright.

Swayam Ramakanth: Thank you. Good afternoon, Jennifer, Scott.

Swayampakula Ramakanth: Thank you. Good afternoon, Jennifer, Scott.

Speaker #4: Thank you. Good afternoon. Jennifer Scott.

Jennifer Bath: Hi, RK. How are you?

Speaker #1: Hi, RK. How are you?

Jennifer Bath: RK, how are you?

Speaker #4: Good, good. So congratulations on all the developments. Obviously, you know, having the second or two recurring revenue licenses is pretty good. But I just have a few questions.

Swayam Ramakanth: Good. Congratulations on all the developments. Obviously, having the second or two recurring revenue licenses is pretty good. I just have few questions, if I may. To start off, of the CAD 15.5 million that you recorded as revenue for fiscal year 2026, what percentage of that revenue comes from the recurring revenue of the first license you have in the books now.

Swayampakula Ramakanth: Good. Congratulations on all the developments. Obviously, having the second or two recurring revenue licenses is pretty good. I just have few questions, if I may. To start off, of the CAD 15.5 million that you recorded as revenue for fiscal year 2026, what percentage of that revenue comes from the recurring revenue of the first license you have in the books now.

Speaker #4: If I may. So to start off you know of the 15 and a half million dollars that you recorded as revenue for 2026 fiscal year 2026 what percentage of that revenue comes from the recurring revenue that that the first license you you you have you know in in in the in the books now?

Speaker #1: Yeah. Okay. I mean, our revenue is almost primarily still fee-for-service work. We signed this agreement early in the middle of this fiscal year.

R. Scott Areglado: Yeah. RK, our revenue is almost primarily still fee-for-service work.

Swayam Ramakanth: Yeah.

Swayampakula Ramakanth: Yeah.

R. Scott Areglado: We signed this agreement early in the middle of this fiscal year. It was a modest amount. Obviously, I don't disclose individual revenue amounts, but it wasn't significant to our overall revenue for fiscal year 2026.

Speaker #1: It was a modest amount and I you know obviously I I don't disclose individual revenue amounts but it was it wasn't it wasn't significant to our overall revenue for fiscal year 2026.

Speaker #4: Okay. Perfect. so.

Swayam Ramakanth: Okay, perfect.

Swayampakula Ramakanth: Okay, perfect.

Jennifer Bath: I wouldn't mind adding just a little something to that, RK.

Speaker #2: I would, I wouldn't mind adding just a little something to that, RK.

Jennifer Bath: Sure.

Swayampakula Ramakanth: Sure.

Speaker #1: Sure.

Speaker #2: Because, yeah, I would say, is it material to the $15.5? No, I wouldn't say it's material. I also wouldn't say it's nothing.

Jennifer Bath: I would say, is it material to the CAD 15.5? No, I wouldn't say it's material. I also wouldn't say it's nothing. It's actually pretty decent, and we're just rev rec-ing it every month as we go. Right? We provided an invoice, they paid that invoice, and now we're rev rec-ing in equal distributions over the course of the timeframe that they have agreed upon in that agreement. I would like to follow up on that with probably the most important part here is, we provided that SaaS model contract to a company who saw the value of the applications that were provided in that contract. They have been using that contract actively-

Speaker #2: It's actually pretty decent, and we're just rev rec'ing it every month as we go, right? So, we provided an invoice, they paid that invoice, and now we're rev rec'ing in equal distributions over the course of the time frame that they have.

Speaker #2: agreed upon in that agreement. And then I would like to follow up on that with probably the most important part here, which is, you know, we provided that SaaS model contract to a company who saw the value of the applications that were provided in that contract.

Jennifer Bath: I would like to follow up on that with probably the most important part here is, we provided that SaaS model contract to a company who saw the value of the applications that were provided in that contract. They have been using that contract actively against that invoice and that payment.

Speaker #2: They have been using that contract actively against that invoice and that payment. And, 100%, the most important part was they worked with us.

Jennifer Bath: against that invoice and that payment. 100%, the most important part was they worked with us, they saw the value. We were doing fee-for-service work first. They turned around and said, We want to actually take a SaaS model license to these applications and take a deeper dive in this, and they did. Of course, going back to everything that I'm pointing to today, that is our primary focus now is, yeah, great, you're seeing it, you're using it. We're rev rec-ing that. We're watching them use the applications. Maybe most important part here to focus on is, of course, now, we're targeting that exact profile for ReefIQ for data management engagement. Back to that thesis, that's really the next step I had asked people to watch for.

Jennifer Bath: 100%, the most important part was they worked with us, they saw the value. We were doing fee-for-service work first. They turned around and said, we want to actually take a SaaS model license to these applications and take a deeper dive in this, and they did. Of course, going back to everything that I'm pointing to today, that is our primary focus now is, yeah, great, you're seeing it, you're using it. We're rev rec-ing that. We're watching them use the applications.

Speaker #2: They saw the value. We were doing fee-for-service work first. Then they turned around and said, "We want to actually take a SaaS model license to these applications and take a deeper dive into this."

Speaker #2: And they did. So, of course, going back to everything that I'm pointing to today that is our primary focus now is, yeah, great, you're seeing it, you're using it, we're reviewing that, we're watching them use the applications. Maybe the most important part here to focus on is, of course, now we're targeting that exact profile for Ref IQ for data management engagement.

Jennifer Bath: Maybe most important part here to focus on is, of course, now, we're targeting that exact profile for ReefIQ for data management engagement. Back to that thesis, that's really the next step I had asked people to watch for.

Speaker #2: And so, kind of back to that thesis—you know, that's really the next step I had asked people to watch for, and that's exactly what we're doing with the dozens of clients who are also utilizing SaaS, our SaaS model. Really, the portal, with the Lens AI applications, as we turn data back as well.

Jennifer Bath: That's exactly what we're doing with the dozens of clients who are also utilizing our SaaS model, really the portal with the LensAI applications as we turn data back as well. That's also our focus for the other client with the newer agreement. Just want to make sure I put that in some full context there.

Speaker #2: And that's also our focus for the other client with the newer agreement. So, just wanted to make sure I put that in some full context there.

Swayam Ramakanth: Yeah. No, thanks for that explanation. Yes, now I understand that since it becomes part of already the programs that the clients have signed up for, it's really difficult to tease out specifically the dollar amount. Probably, I'm assuming that's what you're telling me, and that's understandable. Maybe another way to look at this is, as you continue to increase utilization of the platform in any or all of these programs, I'm trying to think about at least margin. Can we talk through the margins and say, as you continue to increase the utilization, how the margins could expand from here, not only at the gross margin level, but also at the operational level?

Swayampakula Ramakanth: Yeah. No, thanks for that explanation. Yes, now I understand that since it becomes part of already the programs that the clients have signed up for, it's really difficult to tease out specifically the dollar amount. Probably, I'm assuming that's what you're telling me, and that's understandable.

Speaker #4: Yes. Yeah. No. Thanks for that explanation. Yes. No. And I I can I understand that you know since it becomes part of already the the programs that the clients had signed up for it's really difficult to tease out specifically the the dollar amount probably that's I I'm I'm assuming that's what you're telling me and and that that's understandable.

Speaker #4: So has maybe another way to look at this is as you continue to in increase utilization of the platform in in any of in any or all of these programs the how and I'm trying to think about at least margin.

Swayampakula Ramakanth: Maybe another way to look at this is, as you continue to increase utilization of the platform in any or all of these programs, I'm trying to think about at least margin. Can we talk through the margins and say, as you continue to increase the utilization, how the margins could expand from here, not only at the gross margin level, but also at the operational level?

Speaker #4: So, you know, can we talk through the margins and say, like, how as you continue to increase the utilization, you know, how the margins could expand from here—not only at the gross margin level but also at the operational level?

Speaker #1: Yeah. Look the you know SAS one of reasons people like the SAS model subscription is because they do generate high margins. I don't have an exact number because we we still need to understand what the what the compute cost that goes with that would be as they start to engage more with it which would end up in the in the costs but I would still expect it to be you know a high margin business and I think once once we get a couple more clients and I have a sense of where that'll fall I could be able to talk a little bit more about it but I I I would expect it to be very healthy margins.

R. Scott Areglado: Yeah. Look, one of the reasons people like the SaaS model subscription is because they do generate high margins. I don't have an exact number because we still need to understand what the compute cost that goes with that would be as they start to engage more with it, which would end up in the costs. I would still expect it to be a high-margin business. I think once we get a couple more clients and I have a sense of where that'll fall, I could be able to talk a little bit more about it. I would expect it to be very healthy margins.

Speaker #4: Okay. Good. And then on the on the two things happened over the last six weeks or eight weeks now. not only launching of the ref IQ but also the IP that that was was filed.

Swayam Ramakanth: Okay, good. Two things happened over the last six weeks or eight weeks now. Not only launching of the ReefIQ, but also the IP that was filed, the application was filed. As you go forward, how do you plan to pack this together? Is there a way to invite new customers, such that they use that as a separate package, or would that always be included within your services that you already offer to any of your current customers?

Swayampakula Ramakanth: Okay, good. Two things happened over the last six weeks or eight weeks now. Not only launching of the ReefIQ, but also the IP that was filed, the application was filed. As you go forward, how do you plan to pack this together? Is there a way to invite new customers, such that they use that as a separate package, or would that always be included within your services that you already offer to any of your current customers?

Speaker #4: The application was filed. So as you go forward, how do you plan to package this together? And, you know, is there a way to invite new customers such that they use that as a separate package, or would that always be included within your services that you already offer to any of your current customers?

Jennifer Bath: I love that question, RK, because we didn't talk a lot about that on the call. I think it is important for us to make sure that it's extremely clear that, yes, of course, it is something that can be packaged. It's something that I think is more tempting to people who have used our applications, who have used our fee-for-service, who see what a difference that having the connectivity and the context and the meaning have made to the programs. I think in large part if we wanted to point to a few specific but anonymous examples, they have seen that most definitely when we've been able to solve problems that other people couldn't, and that's what drew them deeper into using our platforms, into taking a SaaS model license, or into contracting us to do that type of LensAI work with them.

Speaker #2: I love that question, RK, because we didn't talk a lot about that on the call. And so I think it is important for us to make sure that it's extremely clear that yes, of course, it is something that can be packaged.

Speaker #2: It's something that I think is more tempting to people who have used our applications, who have used our fee-for-service, who see what a difference having the connectivity and the context and the meaning have made to the programs.

Speaker #2: And I think, in large part, if we wanted to point to a few specific but anonymous examples, they have seen that most definitely when we've been able to solve problems that other people couldn't. And that's what drew them deeper, you know, into using our platforms, into taking a SaaS model license, or into contracting us to do that type of lens AI work with them.

Jennifer Bath: I think in large part if we wanted to point to a few specific but anonymous examples, they have seen that most definitely when we've been able to solve problems that other people couldn't, and that's what drew them deeper into using our platforms, into taking a SaaS model license, or into contracting us to do that type of LensAI work with them.

Speaker #2: Just as a quick note, that type of fee-for-service work has actually come to an end. We are now asking people to contract with us either in a partnership model, or they can take a SaaS license to do some of that work on their own.

Jennifer Bath: Just as a quick note, that type of fee-for-service work has actually come to an end. We are now asking people to contract us either in a partnership model or they can take a SaaS license to do some of that work on their own. We're no longer offering piecemeal fee-for-service for people to get introduced to the platform because the platform in and of itself is more mature than it was when we began offering that. Can people come to the table and use these platforms, without going through the channels of right now, where we've distributed SaaS model subscriptions, or we've distributed data back to dozens of clients within LensAI so they can see the applications, or trial the applications.

Speaker #2: We're no longer offering piecemeal, fee-for-service options for people to get introduced to the platform, because the platform itself is more mature than it was when we began offering that.

Speaker #2: But can people come to the table and use these platforms, you know, without, you know, going through the channels of—like right now, where we've distributed SaaS model subscriptions or we've distributed data back to, you know, dozens of clients within Lens AI so they can see the applications or trial the applications? You know, that's just one direction, and that's a really unique way because we have these loyal clients.

Jennifer Bath: Can people come to the table and use these platforms, without going through the channels of right now, where we've distributed SaaS model subscriptions, or we've distributed data back to dozens of clients within LensAI so they can see the applications, or trial the applications. That's just one direction, and that's a really unique way because we have these loyal clients, we have clients just day in and day out where we're turning data back.

Jennifer Bath: That's just one direction, and that's a really unique way because we have these loyal clients, we have clients just day in and day out where we're turning data back. I think the most important part here that we need to emphasize is the fact that utilizing ReefIQ to provide context and to provide meaning isn't limited not only to our clients, it's not limited in almost every other way that you would look at software or applications, or access to technology in potentially being limited. ReefIQ is something that everyone can access, no matter what AI model they're using, right? That's what we really see out there.

Speaker #2: We have clients just day in and day out where we're turning data back. But I think the most important part here that we need to emphasize is the fact that utilizing Ref IQ to provide context and to provide meaning isn’t limited only to our clients. It’s not limited in almost any other way that you would look at software or applications or access to technology as being potentially limited.

Jennifer Bath: I think the most important part here that we need to emphasize is the fact that utilizing ReefIQ to provide context and to provide meaning isn't limited not only to our clients, it's not limited in almost every other way that you would look at software or applications, or access to technology in potentially being limited. ReefIQ is something that everyone can access, no matter what AI model they're using, right? That's what we really see out there.

Speaker #2: It is—Ref IQ is something that everyone can access, no matter what AI model they're using, right? And that's what we really see out there.

Speaker #2: We see a lot of people in the drug discovery business, people in in you know just areas of research and development developing AI models in order to try to do things faster be more accurate save money whatever it might be and what we're finding is they're all running into that same difficulty that same difficulty being that all of a sudden you know they've been training their model they're training their model when their model sees something it's never seen before it hasn't trained on it before it doesn't have the answers and unfortunately that's where these models start to hallucinate and it's not like using chat GPT where you just get back an answer that might be a bit ridiculous you're probably going to flag it and you're going to see it but it was hallucinating its answer to it and it might you know cost you 15 minutes to get it back on track or maybe something you don't recognize is wrong and it cost you an afternoon or a couple of days when this type when hallucination happens at this level in drug discovery it can cost hundreds of millions of dollars it can waste years and if people have never experienced it it's a new target it's a new indication it's a first-in-class molecule they don't know the mechanism of action when they're data when the data is being analyzed and the and then the information coming back isn't accurate it can completely destroy and kill a program and that's where ref IQ definitively comes into play anyone can use it no matter what their AI model is they can literally snap on it can be used most definitively with agentic AI it can be queried directly with generative AI programs and it's compatible with any other platform that anyone has built.

Jennifer Bath: We see a lot of people in the drug discovery business, people in just areas of research and development, developing AI models in order to try to do things faster, be more accurate, save money, whatever it might be. What we're finding is they're all running into that same difficulty. That same difficulty being that all of a sudden, they've been training their model. When their model sees something it's never seen before, it hasn't trained on it before, it doesn't have the answers. Unfortunately, that's where these models start to hallucinate. It's not like using ChatGPT, where you just get back an answer that might be a bit ridiculous. You're probably going to flag it and you're going to see it, but it was hallucinating its answer to it, and it might cost you 15 minutes to get it back on track.

Jennifer Bath: When their model sees something it's never seen before, it hasn't trained on it before, it doesn't have the answers. Unfortunately, that's where these models start to hallucinate. It's not like using ChatGPT, where you just get back an answer that might be a bit ridiculous. You're probably going to flag it and you're going to see it, but it was hallucinating its answer to it, and it might cost you 15 minutes to get it back on track.

Jennifer Bath: Maybe something you don't recognize is wrong, and it costs you an afternoon or a couple of days. When hallucination happens at this level in drug discovery, it can cost hundreds of millions of dollars. It can waste years. If people have never experienced it's a new target, it's a new indication, it's a first-in-class molecule. They don't know the mechanism of action. When the data's being analyzed and then the information coming back isn't accurate, it can completely destroy and kill a program. That's where ReefIQ definitively comes into play. Anyone can use it, no matter what their AI model is. They can literally snap on. It can be used most definitively with agentic AI.

Jennifer Bath: When the data's being analyzed and then the information coming back isn't accurate, it can completely destroy and kill a program. That's where ReefIQ definitively comes into play. Anyone can use it, no matter what their AI model is. They can literally snap on. It can be used most definitively with agentic AI.

Jennifer Bath: It can be queried directly with generative AI programs, and it's compatible with any other platform that anyone has built, and it doesn't have competition in the space to do this. It elevates everyone else's AI models. It is perfectly fine for someone to come to us and say, "ReefIQ is the orchestration layer that we need," and to purchase access to ReefIQ, and then to feel confident that this can be utilized in a secure environment without jeopardizing or threatening the security of their data or the systems that their programs are running within. Absolutely. That's a very important message that we will continue to talk about this year so people can understand the breadth in which this ReefIQ technology can be utilized.

Speaker #2: And it doesn't have competition in the space to do this. So it elevates everyone else's AI models, and it is perfectly fine for someone to come to us and say Ref IQ is the orchestration layer that we need, and to purchase access to Ref IQ, and then to feel confident that this can be utilized in a secure environment without jeopardizing or threatening the security of their data or the systems that their programs are running within.

Jennifer Bath: It is perfectly fine for someone to come to us and say, "ReefIQ is the orchestration layer that we need," and to purchase access to ReefIQ, and then to feel confident that this can be utilized in a secure environment without jeopardizing or threatening the security of their data or the systems that their programs are running within. Absolutely. That's a very important message that we will continue to talk about this year so people can understand the breadth in which this ReefIQ technology can be utilized.

Speaker #2: So, absolutely, and that's a very important message that we will continue to talk about this year so people can understand the breadth in which this Ref IQ technology can be utilized.

Speaker #4: Okay, so one last question from me before I step back into the queue.

Swayam Ramakanth: Okay. One last question from me before I step back and enter it to you.

Swayampakula Ramakanth: Okay. One last question from me before I step back and enter it to you.

Jennifer Bath: Okay.

Speaker #2: Okay.

Speaker #4: In in addition to this you know you you you also have three assets that you're working on the the dengue virus the influenza and the GLP-1 of these three you know o over the next year which ones do you think could could advance enough that either you can attract somebody to help you out in developing further or you would be able to attract enough funding such that you can take this forward itself.

Swayam Ramakanth: In addition to this, you also have three assets that you're working on, the dengue virus, the influenza, and the GLP-1. Of these three, over the next year, which ones do you think could advance enough that either you can attract somebody to help you out in developing further, or you would be able to attract enough funding such that you can take this forward itself?

Swayampakula Ramakanth: In addition to this, you also have three assets that you're working on, the dengue virus, the influenza, and the GLP-1. Of these three, over the next year, which ones do you think could advance enough that either you can attract somebody to help you out in developing further, or you would be able to attract enough funding such that you can take this forward itself?

Jennifer Bath: Oh, that is an interesting question. I think there's a number of points, I'll try to be succinct here in my answers to them. The first one being, the honest answer is, I don't know which one will move the furthest. What's really interesting is we continue to find and build new context around these particular molecules and the diseases that they cause. There's an aspect around that of when do we move something forward a little bit more and, when do we take it and take a look at maybe formulation or presentation of that molecule? We're looking at some of the minute details as we go through. We on the surface make it sound relatively simplistic, right? We're immunizing these animals, we're collecting the sera, we're doing this, we're doing that, we're looking for neutralization, et cetera.

Jennifer Bath: That is an interesting question. I think there's a number of points, I'll try to be succinct here in my answers to them. The first one being, the honest answer is, I don't know which one will move the furthest. What's really interesting is we continue to find and build new context around these particular molecules and the diseases that they cause.

Speaker #2: Oh that is an interesting question. so I think I I think there's an a number of points and I'll I'll try to be succinct here in my answers to them.

Speaker #2: The first one, being the honest answer, is I don't know which one will move the furthest. What's really interesting is that we continue to find and build new context around these particular molecules and the diseases that they cause.

Speaker #2: And so there's an aspect around that of when do we move something forward a little bit more, and, you know, when do we take it and take a look at maybe formulation or presentation of that molecule.

Jennifer Bath: There's an aspect around that of when do we move something forward a little bit more and, when do we take it and take a look at maybe formulation or presentation of that molecule? We're looking at some of the minute details as we go through. We on the surface make it sound relatively simplistic, right? We're immunizing these animals, we're collecting the sera, we're doing this, we're doing that, we're looking for neutralization, et cetera.

Speaker #2: We're looking at some of the minor, minute details as we go through, you know. So we kind of, on the surface, make it sound relatively simplistic, right? Where, you know, we're immunizing these animals, we're collecting the serum, we're doing this, we're doing that, we're looking for neutralization, etc.

Jennifer Bath: Reality is, we're also taking a fine-tuned look at what arms of the immune system are we actually amplifying and are we stimulating? To what extent would we predict MHC class I or class II responses, and in what geographies? What people are likely to give us these responses? To what extent do we understand the type of response that we need as we move through looking at a desired mechanism of action, a desired type of response? That's going to provide lasting immunity or lasting therapy, depending on the product that we're making. Not to get too wordy about that, but it's a little deeper than kind of what we've already provided. The assets right now, as they're moving along, we are quite happy with the way they're moving.

Speaker #2: Reality is we're also taking a fine-tuned look at you know what arms of the immune system are we actually amplifying and are we stimulating and to what extent you know would we would we predict MHC class one class or or class two responses and in what geographies what people are likely to give us these responses and to what extent do we understand the type of response that we need as we move through looking at a desired mechanism of action a desired type of response that's going to provide lasting immunity or lasting therapy depending on the product that we're making so not to get too wordy about that but it's a little deeper than kind of what we've already provided and the assets right now as they're moving along we are quite happy with the way they're moving but there's another caveat here which is like what we've shared is not the full extent of of course what we're working on.

Jennifer Bath: That's going to provide lasting immunity or lasting therapy, depending on the product that we're making. Not to get too wordy about that, but it's a little deeper than kind of what we've already provided. The assets right now, as they're moving along, we are quite happy with the way they're moving.

Jennifer Bath: There's another caveat here, which is like, what we've shared is not the full extent of course, what we're working on. That makes it even more difficult to choose one of those three assets, because certainly some are ahead of others, some are just in validation or in repetition, because we'll never take a single data point or study and lean into that to move it forward. Others have different aspects of how far we plan to move them. Some of them have prospective partners already lined up and waiting, which means we aren't going to move them all the way through if they continue to be successful.

Speaker #2: And so that makes it even more difficult to choose one of those three assets, because certainly some are ahead of others, some are just in validation or in repetition, because we'll never take a single data point or study and lean into that to move it forward.

Speaker #2: And others have, you know, different aspects of how far we plan to move them. Some of them have prospective partners already lined up and waiting, which means we aren't going to move them all the way through if they continue to be successful.

Jennifer Bath: Others have different aspects of how far we plan to move them. Some of them have prospective partners already lined up and waiting, which means we aren't going to move them all the way through if they continue to be successful.

Speaker #2: and when we look at some of the other assets that you know we're moving along that are not you know we haven't really talked about in that we haven't at all talked about in the public domain who's to know if some of those might even leapfrog and move faster so so what I can say RK with certainty is we are focused on these everyday we've built a team and we're continuing to add on to that team in subject matter experts whether it is in the engineering whether it is it is you know biologics experts and immunology and design you know we're continuing to build that team to make sure that as our assets grow we can continue to keep this a priority and and so it is a it is as I mentioned it's one of our major three pillars of focus this year and we are also focused on getting that non-dilutive funding in the door for those assets making sure that we have a ring-fenced structure that makes piping that money directly in as easy as possible for investors and that's a lot of work we have been doing over the last quarter in particular in making sure that that's designed in a way that is optimized for mind walk and for those assets to move forward.

Jennifer Bath: When we look at some of the other assets that we're moving along that we haven't at all talked about in the public domain, who's to know if some of those might even leapfrog and move faster? What I can say, RK, with certainty, is we are focused on these every day. We've built a team, and we're continuing to add on to that team in subject matter experts, whether it is in the engineering, whether it is biologics experts in immunology and design. We're continuing to build that team to make sure that as our assets grow, we can continue to keep this a priority. It is, as I mentioned, it's one of our major three pillars of focus this year.

Jennifer Bath: We've built a team, and we're continuing to add on to that team in subject matter experts, whether it is in the engineering, whether it is biologics experts in immunology and design. We're continuing to build that team to make sure that as our assets grow, we can continue to keep this a priority. It is, as I mentioned, it's one of our major three pillars of focus this year.

Jennifer Bath: We are also focused on getting that non-dilutive funding in the door for those assets, making sure that we have a ring-fenced structure that makes piping that money directly in as easy as possible for investors. That's a lot of work we have been doing over the last quarter, in particular, in making sure that that's designed in a way that is optimized for MindWalk and for those assets to move forward. All of that is kind of front and center in what we're doing, and things are moving along likely and quite well. I think over this fiscal year, we don't know which is going to move the fastest, but we are probably just as excited as you and some of our investors are in seeing how far these go and which ones are moving most quickly to these milestones.

Speaker #2: So all of that is kind of front and center in what we're doing and things are moving along along life likely and or quite well and I think you know over the over the this fiscal year we don't know which is going to move the fastest but but we are probably just excited as you and some of our investors are in seeing how far these go and which ones are moving most quickly to these milestones.

Jennifer Bath: All of that is kind of front and center in what we're doing, and things are moving along likely and quite well. I think over this fiscal year, we don't know which is going to move the fastest, but we are probably just as excited as you and some of our investors are in seeing how far these go and which ones are moving most quickly to these milestones.

Swayam Ramakanth: Perfect. No, thank you. Thanks for taking all my questions.

Swayampakula Ramakanth: Perfect. No, thank you. Thanks for taking all my questions.

Speaker #4: Perfect. No, thank you. Thanks for taking all my questions.

Jennifer Bath: Sure, of course. Thank you, RK.

Speaker #2: Sure. Of course. Thank you, RK.

Speaker #1: The next question is from Dania Benhill from Jones.

Operator: The next question is from Dania Benhel from Jones.

Dania Benhel: Hi. Congrats on the progress, and thank you for taking our questions.

Speaker #5: Hi, congratulations on the progress and thank you for taking our questions.

Danya Ben-Hail: Congrats on the progress, and thank you for taking our questions.

Jennifer Bath: Thanks, Dania.

Speaker #4: Thanks Dania.

Speaker #5: Yeah. First one is, what should we expect for the operating expenses trajectory over the next two quarters?

Dania Benhel: First one is, what should we expect for the operating expenses trajectory over the next two quarters?

Danya Ben-Hail: First one is, what should we expect for the operating expenses trajectory over the next two quarters?

Speaker #4: So I I think you know our our operating expenses as I indicated in my prepared remarks I expect them to increase you know the the work that we're doing on the pipeline assets the continued R&D in RefiQ you know are are all commercial investments we we think are worthy.

R. Scott Areglado: I think our operating expenses, as I indicated in my prepared remarks, I expect them to increase. The work that we're doing on the pipeline assets, the continued R&D in ReefIQ, are all commercial investments we think are worthy. I don't have a specific comment on the percent that it's going to increase, but I would expect them to increase. We're trying to run as tight a ship as we can, and we're going to make commercial investments where we think they're going to generate a return, and obviously try and be mindful of capital allocation and expenses.

Speaker #4: I don't have a specific comment on like the lev the the percent that it's going to increase but you know I would I I would expect them to increase look we're we're trying to run as tight a ship as we can and you know we're going to make commercial investments where we think they're going to generate a return and obviously try and be mindful of of capital allocation and and expenses.

R. Scott Areglado: I don't have a specific comment on the percent that it's going to increase, but I would expect them to increase. We're trying to run as tight a ship as we can, and we're going to make commercial investments where we think they're going to generate a return, and obviously try and be mindful of capital allocation and expenses.

Dania Benhel: Yes. Thank you for that. For the pipeline, what should we expect? Can you give any color or guidance on the clinical data updates, publications, any updates on IND-enabling studies on any of the programs?

Danya Ben-Hail: Yes. Thank you for that. For the pipeline, what should we expect? Can you give any color or guidance on the clinical data updates, publications, any updates on IND-enabling studies on any of the programs?

Speaker #5: Yes, thank you for that. And for the pipeline, what should we expect? Can we give any color or guidance on clinical data updates, publications, or any updates on IND-enabling studies on any of the programs?

Jennifer Bath: We do not have any updates to prepare or to provide here that we haven't already provided, with the exception that we don't have any clinical data for pipeline programs that we have built because we don't currently have pipeline products. There's no update to be had there. I think we've provided our most recent update on dengue, kind of reinforced it here, and we're getting the cross-reactivity from that platform that we desire. That is one that we continue to take a close look at the exact details of what that immune response looks like. We're quite happy in being able to establish that cross-reactive immunity. The next step in that, where we expect to finish, we don't have an exact date. We do have a third-party partner that's doing some further analysis on that, but it'll definitely be over the next couple of quarters.

Speaker #2: We do not have any updates to prepare or to provide here that we haven't already provided with the exception that you know we don't we don't have any clinical data for pipeline programs that we have built because we don't currently have pipeline products and and so there's no update to be had there I think we've provided our most reinforced it here and and we're getting the cross reactivity from that platform that we desire that is one that we continue to take a close look at the exact details of what that immune response looks like we're quite happy in being able to establish that that cross reactive immunity the next step in that where we expect to finish I we don't have an exact date we do have a third-party partner that's doing some further analysis on that but it it'll definitely be over the next couple of quarters I don't think we'll be doing any publications on these molecules just for the sake of you know the fact that any publications that we would do on an internal product at this point in time would jeopardize our IP protection of those molecules and none of these molecules are all the way through IP production and any data that does come out wouldn't have been something that would be included anyway.

Jennifer Bath: That is one that we continue to take a close look at the exact details of what that immune response looks like. We're quite happy in being able to establish that cross-reactive immunity. The next step in that, where we expect to finish, we don't have an exact date. We do have a third-party partner that's doing some further analysis on that, but it'll definitely be over the next couple of quarters.

Jennifer Bath: I don't think we'll be doing any publications on these molecules just for the sake of the fact that any publications that we would do on an internal product at this point in time would jeopardize our IP protection of those molecules, and none of these molecules are all the way through IP production, and any data that does come out wouldn't have been something that would be included anyway. What I can say is it's not impossible for other pipeline products, depending on the partner, that some of those could be in peer review publications. Again, just depending on the partner and the level of disclosure that might have already occurred around those particular molecules historically. What I will say is, as these molecules are moving forward, when there are material updates, we will release them.

Speaker #2: So what I what I can say is it's not impossible for other pipeline products depending on the partner you know that some of those could could be in peer review publications again just depending on the partner and the level of disclosure that might have already occurred around those particular molecules.

Jennifer Bath: What I can say is it's not impossible for other pipeline products, depending on the partner, that some of those could be in peer review publications. Again, just depending on the partner and the level of disclosure that might have already occurred around those particular molecules historically. What I will say is, as these molecules are moving forward, when there are material updates, we will release them.

Speaker #2: historically so what I will say is you know as these molecules are moving forward when there are material updates we will release them but one thing that we're considering quite important is we get a lot of not from our analysts but we do get a lot of requests to just release as much information as possible and release updates as often as possible and oftentimes I don't think there's something that like Dania you or myself would consider to be material updates and that's something that you know giving the updates in between the material updates is something we want to back away from because it doesn't seem it's not it's they're not meaningful right for people like ourselves who understand like you and I who understand you know what really adds value to a molecule as it's moving forward the touch by touch and play by play little things that move in very small increments but don't represent true milestones with regard to the the end game of the product are an area that you know we're we're going to to watch closely and to to back down from just to preserve energy and professionality when it comes to announcing these.

Jennifer Bath: One thing that we're considering quite important is we get a lot of, not from our analysts, but we do get a lot of requests to just release as much information as possible and release updates as often as possible. Oftentimes, I don't think there's something that, like Donya, you or myself would consider to be material updates. That's something that giving the updates in between the material updates is something we want to back away from because they're not meaningful for people like ourselves who understand, like you and I, who understand what really adds value to a molecule as it's moving forward.

Jennifer Bath: That's something that giving the updates in between the material updates is something we want to back away from because they're not meaningful for people like ourselves who understand, like you and I, who understand what really adds value to a molecule as it's moving forward.

Jennifer Bath: The touch-by-touch and play-by-play, little things that move in very small increments but don't represent true milestones with regard to the endgame of the product are an area that we're going to watch closely and to back down from, just to preserve energy and professionality when it comes to announcing these. Every material milestone that we hit, and we will still consider things like strong in vitro readouts and in vivo readouts, anything that's moving us toward IND application as a material update, we will keep everyone posted on those.

Speaker #2: So every material milestone that we hit and we will still consider things like you know you know strong in vitro readouts and and in vivo readouts anything that's moving us toward IND application as a material update we will keep everyone posted on those.

Jennifer Bath: Every material milestone that we hit, and we will still consider things like strong in vitro readouts and in vivo readouts, anything that's moving us toward IND application as a material update, we will keep everyone posted on those.

Dania Benhel: Okay. Thank you very much. Looking forward.

Danya Ben-Hail: Okay. Thank you very much. Looking forward.

Speaker #5: Okay, thank you very much. Looking forward.

Jennifer Bath: Thank you.

Speaker #2: Thank you. Thank you.

Speaker #1: And everyone, at this time there are no further questions. That does conclude our question-and-answer session. It also concludes our conference for today.

Operator: Everyone, at this time, there are no further questions. That does conclude our question and answer session. It also concludes our conference for today. We would like to thank you all for your participation, and you may now disconnect.

Q4 2026 MindWalk Holdings Corp Earnings Call

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