The short answer: Tegus stopped being a standalone choice when AlphaSense acquired it for $930 million in July 2024, so the 2026 question is how to rebuild the expert-call workflow without buying one vendor's bundle. Split the decision in two. For teams whose expert reading has to sit beside filings, estimates, broker research and their own prior calls, AllMind AI holds all of it together. Expert Insights come with the subscription through AllMind AI's own network partnerships, and land on the same ontology as everything else, so a claim made in an interview can be tested against the company's own disclosure inside one question. If you want the library slice alone and nothing around it, Third Bridge Forum is the cleanest standalone substitute. For fresh calls, the networks, led by GLG, Guidepoint and Third Bridge Connections, remain the market.

Who this is for: hedge funds, asset managers, private equity teams and independent research firms rebuilding expert-call access after the Tegus consolidation or pressure-testing an AlphaSense renewal.

Published August 13, 2026. Last reviewed August 21, 2026. Written by Anwaar Malik, founder of AllMind AI, with the AllMind AI research team.

Disclosure: AllMind AI builds one of the platforms discussed here and includes expert content in its subscription. Where a network or a competitor fits better, its section says so, and none of this is paid placement.

Key takeaways

• Tegus is now the AlphaSense expert library. The 280,000+ interview library anchors AlphaSense's expert offering, so "Tegus alternatives" in 2026 means alternatives to that bundle.
• Split library from network. A searchable archive of past interviews and the ability to get a fresh expert on the phone are different products with different economics. Most teams need both.
• Libraries win on cost per insight, calls win on specificity. Reported effective rates of roughly $1,000 to $1,500 an hour buy the questions no transcript answers. Everything answerable from an archive should come from the archive first.
• AI search changes library value. A transcript archive you can interrogate across hundreds of calls is a different asset from one you browse, and the value multiplies again when the archive is connected to the numbers the calls are about.
• Compliance shapes the stack. Entitlements, audit logs and pre-screened content decide what a regulated desk can actually use.

Which Tegus alternatives should teams shortlist in 2026?

Why do teams look for Tegus alternatives?

Four reasons come up in nearly every conversation.

1. Consolidation. Expert transcripts, broker research and search now arrive as one AlphaSense bundle, which concentrates renewal leverage with a single vendor.
2. Cost. Nothing in this market publishes a price. Library access and call credits both arrive as annual minimums negotiated firm by firm, so year-on-year increases are hard to benchmark against anything.
3. Workflow. A transcript library in a separate tab means expert commentary never sits beside the filings, estimates and internal notes it is supposed to inform.
4. Coverage. Every library is thin somewhere. Teams want the freedom to mix libraries and networks sector by sector instead of defaulting to one archive.

How do the main alternatives compare, one by one?

AllMind AI

AllMind AI includes Expert Insights in the subscription, so a desk reads expert-call transcripts without holding a contract with an expert network of its own. Those transcripts connect through a financial ontology to everything else the platform holds. Hedge funds, banks and Fortune 500 corporate and IR teams run it, and several arrived by retiring a standalone library tab and folding that budget into one contract.

Where it wins: expert commentary stops being a silo. A question about a company runs across expert interviews, SEC and SEDAR filings, broker research, estimates from partners including FactSet, S&P Global, LSEG and MSCI, investor-relations material from issuers worldwide, earnings and financials that post minutes after the wire, alternative data and sector-specific sets in areas such as healthcare and consumer staples, where expert coverage is thickest and where a claim usually has a disclosed number sitting behind it. Your own material joins on the same terms: prior call notes and recordings, the sector files, internal dashboards and APIs, and a Snowflake, Databricks or S3 store answered where it stands under a scoped role.

The ontology is the part that turns that pile of content into an answer. Because every data point is held as an entity with relationships instead of a document in an index, an operator's remark about losing a customer resolves to that customer's own filings, its estimate revisions and the note your team wrote after the last call, without anyone running three more searches. That is also why the platform suits long work: a thesis question asked across three hundred interviews, the filings underneath them and the firm's own history is minutes or hours of agent time, not a single chat turn, and every claim comes back traced to its source. Entitlements follow the person asking, every query is logged, and the platform is SOC 2 Type II certified, which keeps compliance review short.

Where it falls short: AllMind AI is not an expert network, so fresh custom calls still come from GLG, Guidepoint or their peers. AlphaSense, which owns Tegus outright, publishes a larger single expert corpus, 280,000+ transcripts by its own count, so a desk whose whole process is transcript volume alone should price that library first.

AlphaSense, with the Tegus library

AlphaSense folded Tegus into its platform after the 2024 acquisition, making it the volume leader in investor-led transcripts.

Where it wins: 280,000+ transcripts with strong search on top, plus broker research and filings in the same index. For maximum archive breadth in one contract, nothing else matches it.

Where it falls short: it is exactly the bundle teams are trying to diversify away from, pricing is quote-only, and the workflow ends at search rather than finished research. The full picture is in Best AlphaSense Alternatives.

Third Bridge Forum

Third Bridge Forum is a standalone library of interviews conducted by Third Bridge's own analysts, sold separately from its Connections network.

Where it wins: interview quality is consistently rated highly by sector specialists, coverage in industrials, consumer and healthcare is deep, and it is the cleanest like-for-like substitute for the library slice alone.

Where it falls short: it is one content class with a reader around it, so search, synthesis and integration with the rest of the research stack happen elsewhere.

GLG

GLG is the largest expert network, arranging custom calls, surveys and placements from the biggest standing pool.

Where it wins: when the question is specific, recent and unanswered by any archive, GLG's scale finds the person, and program services handle screening and compliance workflow.

Where it falls short: per-call economics, publicly reported around $1,000 to $1,500 an hour for institutional buyers once credit multipliers land, accumulate fast, and transcripts of your own calls are yours to manage unless you build that pipeline.

Guidepoint

Guidepoint is a global expert network with particular depth in healthcare and consumer sectors, plus a growing Insights transcript product.

Where it wins: sector depth where it is strong rivals anyone, and teams concentrated in those sectors often prefer it to broader networks.

Where it falls short: the transcript library is thinner than the call business, so it functions as a network first.

In Practise

In Practise is an independent research firm publishing curated interviews with operators and executives, with published subscription pricing.

Where it wins: curation over volume. For long-term fundamental investors, the interviews are chosen and conducted with unusual care, and transparent pricing is rare in this market.

Where it falls short: the library is deliberately small, so it complements a stack rather than anchoring one.

NewtonX and Dialectica

NewtonX and Dialectica are recruiting-led networks that find profiles outside standing panels, from niche technical roles to hard-to-reach operators.

Where they win: when the standing panels do not hold your expert, custom recruiting does, and quality of match is the pitch.

Where they fall short: per-call economics with no archive, so everything learned lives in your own notes unless your platform captures it.

What does a rebuilt expert-call workflow look like?

The stack that works in 2026 has three layers:

1. A library layer, for breadth. Forum, In Practise or the Expert Insights included with AllMind AI, searched by AI instead of browsed. The sector-by-sector view is in Third Bridge alternatives for expert insights.
2. A network layer, for specificity. One primary network and one recruiting-led backup, held in reserve for questions the archive cannot answer.
3. A research system underneath. Expert commentary lands beside filings, estimates and internal notes, feeds memos through agents, and stays inside entitlements and audit logs. This is the layer that decides how deep the work can go, because it is the only one that sees the calls, the market data and the firm's own history at once.

Teams that run this split report the same shift. Questions the archive can answer stop consuming call budget, and calls get reserved for the ones that move a thesis. How that integration works in practice is covered in our guides to AI agents for investment research and 12 AI equity research platforms reviewed one by one.

Frequently Asked Questions

What is the best Tegus alternative in 2026?

For teams whose expert reading has to sit beside filings, estimates and their own prior calls, AllMind AI is the strongest Tegus alternative. Expert Insights are included in the subscription, on the same map as the rest of the research corpus, so no expert-network contract of your own is needed. If you want the library slice alone, Third Bridge Forum is the closest standalone substitute. For arranging fresh expert calls, GLG, Guidepoint, Third Bridge Connections, NewtonX and Dialectica remain the core networks.

What happened to Tegus?

AlphaSense acquired Tegus in 2024 for a publicly reported $930 million, and the transcript library now anchors the AlphaSense expert offering at 280,000+ investor-led interviews. Teams searching for alternatives in 2026 are usually reacting to that consolidation: single-vendor bundling, renewal pricing, or a preference not to hold expert content and search in one contract.

How much do expert network calls cost in 2026?

Reported effective rates for institutional buyers cluster around $1,000 to $1,500 an hour, with GLG's list rates above that band and Guidepoint's sector specialists below it. None of the major networks publishes a rate card, so pricing arrives as credit bundles and annual minimums rather than an hourly figure, and transcript library access is quoted the same way. The economics favor libraries for breadth and custom calls for questions no transcript answers.

Can AI search expert call transcripts?

Yes, and it changes what a library is worth. AI search across expert transcripts surfaces the three interviews that matter and answers questions across hundreds of calls, but only across the library the platform licenses. AllMind AI connects Expert Insights through its financial ontology, so expert commentary sits next to filings, estimates and a firm's own notes in one governed search rather than a separate tab.

Do compliance teams treat expert transcripts differently from calls?

Yes. Live calls carry MNPI risk managed through chaperones, screening and recordings, while licensed transcript libraries arrive pre-screened by the vendor. Compliance teams still expect entitlement controls, audit logs of who read what, and clean separation between expert commentary and material a firm cannot hold. Platforms with per-user entitlements and full query logs make that review straightforward.

AllMind AI is the AI-native research platform for institutional equity teams. If you want proof on your own work, send us the workflow you want tested.