AllMind vs Model ML
AllMind is an AI research system for institutional investors: the premium dataset classes sit inside the platform, connected as entities and relationships by a financial ontology.
Model ML is an agentic workflow platform whose agents run over the systems and subscriptions a firm licenses.
Both produce Word, PowerPoint and Excel, so the split is who owns the content underneath.
Carries the research content inside the platform, joins it to the firm’s own Snowflake, Databricks and S3 through a scoped IAM role, then builds the model, memo and deck with every number traced to its passage.
Runs agents over what the firm already licenses through Workflows, Grids, Document Review, Chat, Notetaker and Agentic Dashboards, with Word, Excel, PowerPoint and Teams plug-ins and agents other MCP-compatible tools can call.
If the LSEG, Capital IQ, FactSet, PitchBook, Preqin or Third Bridge entitlements are in place and the bottleneck is producing the deliverable, Model ML. If the content is the bottleneck, AllMind.
Feature by feature
Data and entitlements
Premium dataset classes inside the platform
- AllMind
- Supported
- Model ML
- Filings owned, market data on your license
Broker research library
- AllMind
- Aftermarket, on a delay
- Model ML
- Not documented
Expert-call transcripts
- AllMind
- Supported
- Model ML
- Third Bridge license
Private-fund performance data (IRR, TVPI, DPI)
- AllMind
- Not documented
- Model ML
- Preqin, PitchBook
Warehouse queried in place
- AllMind
- Snowflake, Databricks, S3
- Model ML
- Snowflake via MCP
Live market and fundamental data included
- AllMind
- 40+ feeds; actuals and estimates
- Model ML
- Your own LSEG license
Document corpus scale published
- AllMind
- 750M+ documents
- Model ML
- No platform figure; Captide 2.5M at acquisition
Research and analysis
Financial ontology of entities and relationships
- AllMind
- Supported
- Model ML
- Not documented
Supply-chain graph several nodes out
- AllMind
- Supported
- Model ML
- Not documented
Batch analysis grid across many companies
- AllMind
- Supported
- Model ML
- Supported
Cited live web search
- AllMind
- Live news, not open web
- Model ML
- Perplexity Sonar
Deliverables
Excel models with live formulas
- AllMind
- Supported
- Model ML
- Supported
Edits existing PPTX, DOCX and XLSX
- AllMind
- Supported
- Model ML
- Supported
Exports into a firm’s own deck format
- AllMind
- Supplied templates
- Model ML
- Company-stated
Automated deck and model error check
- AllMind
- Verification pass
- Model ML
- AutoCheck
Automation and interoperability
Event-triggered runs
- AllMind
- Supported
- Model ML
- Supported
Published breadth per automation
- AllMind
- Up to 200 companies (AllMind states)
- Model ML
- Not published
Agents callable from other MCP-compatible tools
- AllMind
- Not supported
- Model ML
- Supported
Word, Excel, PowerPoint and Teams plug-ins
- AllMind
- Not documented
- Model ML
- Supported
Security and governance
SOC 2 Type II
- AllMind
- Supported
- Model ML
- Supported
ISO 27001 certified
- AllMind
- Targeted Q1 2027
- Model ML
- States certification
Per-user entitlements that agents inherit
- AllMind
- Supported
- Model ML
- Not documented
Deploy into your own infrastructure
- AllMind
- Not documented
- Model ML
- Supported
Commercials and footprint
Published list pricing
- AllMind
- Not supported
- Model ML
- Not supported
Named public customers
- AllMind
- 6 firms, plus a Fortune 100 E&P company
- Model ML
- PwC and Deloitte (company-stated)
Ties are shown as ties, and the seven rows Model ML wins are marked as wins. Every mark reflects what the two vendors document publicly as of August 30 2026, so “Not documented” means a capability is not publicly documented rather than proven absent. Model ML’s SOC 2 Type II and ISO 27001 marks are its own statements: neither its security page, its homepage nor its trust center publishes a certificate, a certificate number, an auditor or an audit report. AllMind’s “up to 200 companies” figure comes from its own compare pages, and /platform/agent-studio states no cap.
See AllMind on your own coverage→What AllMind owns that a workflow layer has to license
Most of Model ML’s market data arrives on your license, not its own
Most of what Model ML reads is data your firm licenses, not data it owns. The LSEG announcement of July 18 2026 states the condition plainly: if you have an LSEG license, you can start using it inside Model ML today. Third Bridge is the same shape, scoped since September 2025 to Third Bridge subscribers. The Capital IQ, FactSet, PitchBook and Preqin announcements name the data and say nothing about entitlement. Filings and disclosures are the exception Model ML owns outright, through its February 2026 acquisition of Captide.
AllMind is built the other way round. Its 6,800+ premium data sources are classes inside the platform: S&P, FactSet, LSEG and MSCI data, global investor-relations data, live news from thousands of sources, live earnings and financials within minutes, alternative data, and Expert Insights, a shipped content class a desk reads without an expert-network contract of its own. The exception on this side is broker research, where live embargoed research runs on the firm’s own RMS entitlement and aftermarket research is included on a delay that varies by broker.
An ontology answers the supplier question a document search cannot
The supplier question two nodes out needs a map of relationships, not a better document search. AllMind connects every data point, internal and external, as entities and relationships, so an agent traverses the graph instead of ranking passages. The firm’s own tables land in that same graph: Snowflake, Databricks and S3 connect through a scoped IAM role and are queried where they sit, with Google Drive and OneDrive folder sync on Data Rooms. The coverage limit is public: EDGAR, SEDAR+ and global filings, across 18 live markets rather than worldwide.
Model ML does something adjacent, not the same thing. Grids runs many prompts in parallel across a set of documents with source attribution on each cell, and since July 19 2026 the company says it queries Snowflake through Snowflake’s own managed MCP server, so existing permissions carry over. That is parallel extraction with a clean audit trail. It is not a maintained map of how companies relate to each other, and Model ML does not claim one.
Model ML owns the Office surface, AllMind owns the corpus behind it
Model ML has spent 2026 pushing the agent into the applications the analyst has open. Plug-ins for Word, Excel, PowerPoint and Teams shipped on July 18 2026 and the agent answers when tagged in a Teams channel. AutoCheck reads a deck for logic gaps and calculation errors, Excel Agent Review hunts broken links and hardcodes, and since July 21 2026 Model ML supports MCP in both directions, so its agents can be called from Claude or Copilot. AllMind publishes no MCP server and no Office plug-in.
What AllMind puts behind the deliverable is a governed corpus and a paper trail: decks from 20+ investment-bank templates, Word memos, Excel models with live formulas, and editing of existing PPTX, DOCX and XLSX, with every number traced to its source passage, the calculation visible, a verification pass before a report ships, and per-user entitlements agents inherit and can never widen. The template caveat is real: AllMind builds into a supplied template, so a bespoke house format still needs a formatting pass.
Where Model ML is strong
Model ML is a serious, well-built platform, and 2026 was a strong year for it. PwC is scaling co-developed agents for transaction work and document review globally, the company says (July 13 2026), and Deloitte brought it into its M&A practice weeks later (July 28 2026). Tech.eu named both firms independently on August 11 2026, the day HSBC Asset Management took a stake through its flagship VC strategy. Its advisory bench is former bank chief executives and chairs: Axel Weber, Sir Noel Quinn, Mark Machin, Philipp Rickenbacher.
It is well built where it matters to a deal team. Operator drafts models, decks and memos end to end, AutoCheck reads a presentation for logic gaps and calculation errors, and the Office and Teams plug-ins put the agent in the file the associate has open. It states ISO/IEC 27001 certification, offers deployment into a client’s own infrastructure, and supports MCP in both directions. AllMind’s focus is different: bringing the institutional data and content in, and acting on it end to end.
Two tools, two different jobs
AllMind
The AI research system for institutional investors
A governed research platform that carries its own content. 6,800+ premium data sources covering S&P, FactSet, LSEG and MSCI data, global investor-relations data, live news from thousands of sources, live earnings and financials within minutes, alternative data and Expert Insights sit inside the platform, connected as entities and relationships by a financial ontology.
The firm’s own Snowflake, Databricks and S3 join that graph through a scoped IAM role, queried in place. Agents run long, multi-step work over both and produce the Excel model, Word memo and PowerPoint deck, every figure traced to its passage.
Model ML
The agentic workflow platform for financial services
An agentic workspace for financial services, which the company calls an agentic operating system, positioned as “Your Finance Agent. Wherever You Are.” Its surfaces are Workflows, Grids, Document Review, Chat, Notetaker and Agentic Dashboards.
Its agents run over the systems and subscriptions a firm already holds: LSEG, S&P Capital IQ, FactSet, PitchBook, Preqin, Third Bridge, Perplexity Sonar and Snowflake. Filings and disclosures are the content it owns outright, through its February 2026 acquisition of Captide. All from the company’s own announcements, as of August 2026.
What each one is good at, and what it costs you
AllMind
- S&P, FactSet, LSEG and MSCI data, live earnings within minutes and alternative data, inside the platform
- Expert-call transcripts with senior operators, read from Chat, a tab of their own and the Data Room
- Every data point is connected as entities and relationships, so agents traverse rather than retrieve
- Internal Snowflake, Databricks and S3 tables are joined to the external corpus, not copied out
- Agents run for minutes or hours across many sources, not one-shot chat answers
- A verification pass re-checks figures before a report ships, and every access is logged
- A deck lands in a supplied investment-bank template, so a bespoke house format needs a formatting pass
- ISO 27001 is targeted for Q1 2027, the one place Model ML is ahead on a vendor questionnaire
- Aftermarket broker research arrives on a delay; live embargoed research needs the firm’s own RMS entitlement
Model ML
- Word, Excel, PowerPoint and Teams plug-ins since July 18 2026, with the agent answering when tagged
- Its agents can be called from Claude, Copilot or a firm’s own internal tools
- States ISO/IEC 27001 certification and offers deployment into the customer’s own infrastructure
- AutoCheck reviews a deck for logic gaps, formatting and calculation errors before a partner sees it
- Preqin fund performance and PitchBook private-company data are named connectors
- Owns its filings and disclosure corpus after acquiring Captide in February 2026
- LSEG and Third Bridge content reaches the platform on the firm’s own license
- No broker research library, financial ontology or supply-chain graph is publicly documented
- The ISO 27001, SOC 2 and GDPR badges publish no certificate, auditor or audit report
- No published price, and no procurement directory carries a figure to check a quote against
What AllMind and Model ML actually cost
AllMind
Quote-based, with the content inside the contract
Pricing is set in a sales conversation. There is no self-serve checkout and no monthly plan, so a non-institutional buyer is better served by a self-serve tool. What the contract covers is the platform and the premium dataset classes together, with the exception of live embargoed broker research, which runs on the firm’s own RMS entitlement.
- List pricing
- Not published; quote-based
- Self-serve checkout or monthly plan
- Neither
- Premium dataset classes
- Inside the platform
Model ML
No published price, and no outside estimate either
Model ML’s own machine-readable Q&A endpoint answers this directly: “We do not publish list pricing”, the buying motion is “sales-led through demos and contact flows”, and “commercial terms are scoped to each individual engagement”. There is no pricing page on modelml.com, and no procurement directory we checked carries a figure for it either.
- Pricing page on modelml.com
- No /pricing route
- Third-party estimate
- None we can stand behind
- Data subscriptions it reads
- LSEG and Third Bridge need your own license
What changes the quote
On the AllMind side: seats, which internal systems are connected, and which entitled content classes are switched on. On the Model ML side: seats, which surfaces and plug-ins are switched on, the deployment shape, how much of the work is long-running agent time, and the data the firm may have to license separately.
Model ML runs its own Composite benchmark, which prices finance tasks in dollars per task, so agent run volume is a cost the vendor itself models. The benchmark holds every model inside Model ML’s own agent harness, which is why its scores are not reprinted here.
The two contracts are not like-for-like. One budget line includes the content; the other sits at least partly on top of it. Model ML states the entitlement condition explicitly for LSEG and Third Bridge, and its Capital IQ, FactSet, PitchBook and Preqin announcements are silent either way, so ask which of those it passes through and which you must already hold before you compare the two quotes.
Which one you want, task by task
Turn the diligence folder for this carve-out into a first-draft IC memo and a 30-slide book in our house format, by Friday.
Model ML says it exports Grid content into a firm’s own format, logos and layouts included, and runs AutoCheck over the deck for logic and calculation errors. AllMind’s deliverables land in a supplied template, so a bespoke format still needs a formatting pass. Ask both vendors to demo your template.
Track guidance changes across my 120-name coverage list and put the deltas in my inbox the morning after each print.
AllMind’s compare pages state up to 200 companies in a single automation, and live earnings and financials are available within minutes as a dataset class inside the platform rather than a subscription licensed separately. Model ML schedules and event-triggers agents too, but the earnings feed has to come from somewhere.
Which names in the book are two suppliers away from a single Taiwanese fab, and what did management say about it?
The ontology holds companies, suppliers and customers as entities and relationships, so the agent traverses the chain several nodes out and then lands on the transcript passage. Model ML’s Grids runs the extraction across documents you point it at, which answers a different shape of question.
Run the same exposure analysis over our Snowflake tables and an external market view, without leaving Excel and Teams.
AllMind connects Snowflake, Databricks and S3 through a scoped IAM role, queries them in place and joins them to its external corpus through the ontology. Model ML reaches Snowflake through Snowflake’s managed MCP server and is the one that lives inside Excel and Teams. A desk doing this weekly often runs both.
AllMind and Model ML reward different edges: owning the content and the relationships inside it, or owning the workflow and the last mile of the deliverable.
Choose AllMind when the bottleneck is the research itself: premium dataset classes, Expert Insights transcripts and live earnings within minutes inside the platform, joined to Snowflake or Databricks and connected as entities and relationships, so an agent can walk a supply chain rather than retrieve documents about one.
Choose Model ML when the data question is settled and production is the constraint: the work lands in a house-format deck, the team lives in Teams and Excel, or a stated ISO 27001 certification and own-infrastructure deployment are hard requirements.
AllMind vs Model ML, answered
Model ML publishes no price, and no credible outside estimate exists either. The company’s own machine-readable Q&A endpoint says it does not publish list pricing, the buying motion is sales-led, and commercial terms are scoped to each engagement. There is no pricing page on modelml.com, and Vendr and Sacra carry no entry as of August 30 2026, so anyone quoting you a seat price is guessing.
Budget two lines: the Model ML contract, and the data subscriptions it reads. LSEG and Third Bridge state the entitlement condition; the Capital IQ, FactSet, PitchBook and Preqin announcements are silent, so ask. AllMind is also quote-based, with the dataset classes inside the platform.
See AllMind on your own coverage
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