Tegus Alternatives in 2026: Expert Calls, Models and Filings

For the models and filings work Tegus used to do, the best alternative is Kepler. We assemble every company’s statements from its own XBRL with each cell cited to the line, read every filing, transcript and IR document in full before anyone asks, and our engineers build your firm’s ontology so your definitions, models and notes shape every answer and every number is computed in code.

Tegus did three jobs for investors: expert-call transcripts and calls, ready-made company models, and filings research. Since 2024 all three have lived inside AlphaSense. This page takes each job in turn. For expert calls the right replacement is another expert network, and the best ones are below; for models and filings, Kepler is our pick.

We build Kepler, so it’s listed first and labeled. Facts about other vendors come from their own sites, press releases and public reporting, checked in November 2026 and linked inline.

What happened to Tegus

AlphaSense agreed to buy Tegus in June 2024 and completed the acquisition that July. Tegus had bought Canalyst, the Vancouver company behind more than 4,000 analyst-built models, in August 2022, and BamSEC, the filings search tool Tegus users knew, is part of AlphaSense too.

As of November 2026, tegus.com tells visitors that “Tegus is now part of AlphaSense” and lists what came across: 300,000+ Tegus expert transcripts, Tegus expert call services, 4,000+ pre-built Canalyst models, a 500M+ document library and 1,500 broker partners. Inside AlphaSense, the transcripts are branded Tegus Expert Insights, the live calls Tegus Expert Call Services, and the models sit in its financial data module. BamSEC still sells on its own at $69 a month billed annually and carries the line “BamSEC is now part of AlphaSense.”

Why teams look for Tegus alternatives

• The bundle. Tegus content now comes as part of an AlphaSense contract. Teams that bought Tegus for one job find themselves pricing a much larger platform. What users say: “They bought Tegus/BamSEC but it’s like $7k more to bundle it all vs leaving as-is,” a research analyst at an asset manager wrote on Wall Street Oasis in January 2025.
• Someone else’s model structure. Canalyst models are built and updated by Canalyst’s analysts in a fixed layout. AlphaSense’s support guide tells users not to delete Canalyst rows, columns or worksheets, or the Updater that refreshes the model may stop working. That’s a fair trade for speed, and a constraint for a PM who wants the model built the firm’s way.
• The firm’s own data. Internal models, research notes, CRM history and portfolio data hold most of what a firm knows. Tegus was built around expert content and public filings, so that material lived somewhere else.
• Numbers they can defend. Every figure that lands in a model or an IC memo has to trace to a page and line, with the arithmetic visible. Even with table tools, analysts still clean the output and spot-check line items by hand. What users say: “It’s not the cleanest output (get 3 month data next to 6 or 9 month) but doesn’t take long to clean either. Then I just spot check random line items and make sure they match,” a hedge fund analyst wrote on Wall Street Oasis in 2024, about tables pulled from BamSEC and similar tools.

Tegus alternatives at a glance

Tool	Best for	Tegus job it replaces	Your firm’s data	How numbers are sourced
Kepler	Models and filings work on your firm’s definitions	Models and filings	Your firm’s ontology, every document read in full	Computed by code, cited to page, line or cell
AlphaSense	Keeping Tegus content in a larger library	All three	Connectors to SharePoint, Box and other stores	Canalyst models and standardized financials; AI answers cite source passages
Guidepoint	A large transcript library plus live calls	Expert calls	Not the focus	The transcript itself
Third Bridge	Expert transcripts inside your AI tools	Expert calls	Not the focus	The transcript itself
AlphaSights	Custom calls with an on-demand library	Expert calls	A private library for your own transcripts	The transcript itself
In Practise	Long-form interviews on quality companies	Expert transcripts	No	The transcript itself
Daloopa	Source-linked data points for your own templates	Models	Your own Excel models	Extracted, each point linked to its document

The best Tegus alternatives

1. Kepler (our pick for models and filings)

We build Kepler.

Best for: hedge funds, long-only teams and research desks that want company models, filings research and their own house view in one place, with every number provable.

The models half of Tegus solved a real problem: nobody wants to key ten years of segment data into Excel by hand. The filings half solved another: finding the one table or sentence that matters across thousands of documents. Both still leave the analyst doing the hard part, which is applying the firm’s own definitions, checking each figure against the filing and keeping the model current. We built Kepler to do that part with you.

Our engineers built this layer before at Palantir. On site with your team, they build your firm’s ontology: each company, segment, holding and peer set resolves to one record, and terms like adjusted EBITDA, organic growth or net debt to EBITDA carry your firm’s definition. Public data arrives already loaded: 26M+ SEC filings across 20+ form types with full text and XBRL, 40M+ IR documents and earnings call transcripts (transcripts come from Quartr, our partner), market data and news, for 14,000+ companies in 120+ countries. Extraction models we train read every page at ingest, tables and scanned exhibits included, and store each fact with its value, scale and unit beside the passage it came from. In held-out tests they read tagged facts at the right scale 99.4% of the time (Stop Paying to Forget).

Statements assemble in code from each filer’s own XBRL, with no model in the path, as originally filed or as restated. That matters: in our paper Reclassified to Conform, 194 of 200 companies reshaped a statement in ways XBRL tags can’t follow, so we rebuild each history to keep every line’s meaning stable across years. Every cell opens the page and line behind it, and every calculated figure opens its formula and inputs. Citations are matched to their source before you see them, and when two sources disagree you see both. Ask the same question twice and you get the same number.

The work then runs on its own. Agents refresh your models the morning a company files, flag guidance changes with the exact quote, and send the changes to Excel, PowerPoint, Slack, Claude or ChatGPT. Your playbooks, such as the earnings update in your PM’s format, are saved once and applied every time, and your engineers can build on the same engine through our API and MCP server.

Why it’s our pick for the models and filings work

• Statements and KPIs with every cell cited, as filed or as restated, on any date.
• Your model, your structure: your firm’s definitions and templates, applied to every company you cover.
• Complete answers from the filings. Every 10-K, 10-Q, 8-K, proxy and exhibit is read in full, so a question returns every match, not the top hits.
• Agents you can leave alone, updating models and comps when companies file and acting exactly as the person who set them up.
• Your own documents alongside public data: research notes, internal models, CRM and data rooms, connected read-only and resolved into your ontology.
• Kepler everywhere: the app, Excel, PowerPoint, Word, Claude, ChatGPT, Slack and the Kepler API.
• Your rules built in: one permission check on every read, every query logged with its lineage, SOC 2 Type II, our cloud or yours (security).

Questions former Tegus users bring to Kepler

• “Build Nvidia’s segment and geographic revenue history for the last 12 quarters, as filed and as restated, with every cell cited.”
• “Every 10-K in our consumer coverage that added a risk factor about tariffs this year, with the new language and the prior year’s.”
• “When anyone in our semis book files a 10-Q, update inventory days on our definition and tell me who moved most.”

“Every other AI tool I’ve tried misses what’s buried in the footnotes. Kepler has read every filing, so nothing slips past it.” (Managing Director, multi-billion dollar fund)

Not the right fit if: your team’s main use of Tegus was talking to former executives and reading what experts said. For that work, pick one of the expert networks below.

Try it on a company you model at app.kepler.ai, or book a demo on your coverage list.

2. AlphaSense

Best for: teams that want Tegus transcripts, Canalyst models and BamSEC alongside broker research in one subscription.

Staying put is a real option. AlphaSense now folds the Tegus library into a search that covers more than 500 million documents and research from 1,500 broker partners, according to tegus.com. Its financial data module adds standardized financials, consensus estimates and KPI-rich Canalyst models that update in Excel. SuperAnalyst, its agent, launched on October 6, 2026: given one objective, it plans the work, reconciles evidence, runs code and produces memos, models and monitoring dashboards.

What users say: “Tegus was a fantastic standalone platform - BamSEC was an incredible product because it was simple and it just worked - but when AS acquired it, they didn’t port over all the same useful features,” wrote a G2 reviewer in investment management in October 2024 (AWS Marketplace, G2 reviews).

Trade-offs: AlphaSense doesn’t publish prices. SpendHound reports average spend of $10,131 a year for smaller customers and $139,455 for enterprise customers, and Vendr notes that contracts commonly auto-renew unless canceled 60 to 90 days ahead. More options are in our AlphaSense alternatives guide.

3. Guidepoint

Best for: teams that want a large independent transcript library alongside live expert calls.

Guidepoint says its library holds 130,000+ expert transcripts covering 80,000+ companies, with 7,000 new transcripts a month, each reviewed by its compliance team. Its network of 2 million vetted experts handles live calls and surveys, and AskGP answers questions across the library with traceable attribution, inside Guidepoint360 or through an API or MCP server.

Trade-offs: expert content only. Filings, models and financial data come from somewhere else.

4. Third Bridge

Best for: teams that want expert transcripts inside the AI assistant they already use.

Third Bridge built an MCP server that puts 100,000+ expert transcripts into large language models directly, alongside its Library, which covers more than 75,000 public and private companies. It also runs bespoke expert calls, surveys and data feeds. Its interviews are investor-led and analyst-led, and its private-company coverage includes maps of each company’s value chain.

Trade-offs: like Guidepoint, it replaces the expert half of Tegus only.

5. AlphaSights

Best for: teams that lean on custom expert calls and want an on-demand library as a supplement.

AlphaSights is best known for sourcing experts fast for bespoke calls. Its AlphaNow library adds hundreds of company one-pagers and investor-led call transcripts each week, every transcript arrives with a free AI call summary, and AlphaGPT answers questions across the library in natural language. A private library hosts your own call transcripts for the rest of the team.

Trade-offs: the on-demand library is a supplement to its calls business. Expect a narrower archive than a library-first vendor.

6. In Practise

Best for: long-term investors who read deep interviews on a smaller set of high-quality companies.

In Practise interviews former executives, customers, competitors and suppliers of US and European companies it considers high quality, and publishes its own analysis of each interview, plus a weekly newsletter. A small group of fund managers also runs partner interviews that every subscriber can read, published as text with the partners kept anonymous.

Trade-offs: depth over breadth. Coverage is selective by design, so it won’t replace a broad library for a generalist team.

7. Daloopa

Best for: analysts who want source-linked historical data points to drop into their own model templates.

Daloopa covers 6,000+ public companies with up to 14 years of history, each data point hyperlinked to the filing or presentation it came from. Its Excel add-in updates models after a print, Scout (an Excel agent that became generally available in September 2026) builds and updates models, and an MCP connector brings the data into Claude, ChatGPT and Microsoft 365 Copilot. Its plans page lists a free tier with up to three data sheets and paid plans without published prices.

Trade-offs: a data supplier, so the analysis, the firm’s definitions and the write-up live in your own spreadsheet or assistant. See Daloopa vs Canalyst for a closer comparison.

What Tegus does well

Tegus built one of the best-known expert transcript libraries on the buy side, and its call service made it easy to turn a transcript into a live conversation. Inside AlphaSense, that content now sits in the same search as broker research, filings and Canalyst models. Expert-call transcripts are licensed content, so firms that rely on them keep an expert network or library for that reading.

Kepler vs Tegus for models and filings

	Kepler	Tegus (Canalyst models and BamSEC, inside AlphaSense)
Company models	Statements from each filer’s XBRL plus cited KPIs, in your firm’s own templates	4,000+ pre-built models in Canalyst’s layout
Where each number comes from	Pulled from the filing and computed by code	Entered by Canalyst analysts from primary documents, then QA-checked
What a citation opens	The exact page, line or cell, with the formula for calculations	Source-file links in the guidance tab and update log; audit to source with the Premium add-in
As filed vs as restated	Either, on any date	Maintained by Canalyst’s analysts; changes recorded in the update log
Your firm’s definitions	Built into your ontology, applied to every company	Your own edits inside the model
Filings research	Every document read in full; complete lists, not top hits	Full-text search, table downloads and alerts
Your own documents	Notes, models, CRM and data rooms in your ontology	Internal content searchable through AlphaSense connectors
Work that runs on its own	Agents update models and send changes when a company files	Model updates after filings; SuperAnalyst monitoring
Where it works	App, Excel, PowerPoint, Word, Claude, ChatGPT, Slack, API	AlphaSense app, Excel add-ins

How to choose a Tegus alternative

Start with the job you’re replacing:

• Expert calls and transcripts: Guidepoint for library breadth, Third Bridge to read transcripts inside your AI assistant, AlphaSights for custom calls, In Practise for depth on fewer companies.
• Company models: Kepler, if you want statements and KPIs cited to the line in your own structure; Daloopa, if you want source-linked data points for templates you maintain.
• Filings research: Kepler, which reads every filing in full and answers with the complete set.
• Everything in one subscription: AlphaSense, where Tegus already lives.

Then test on live work. Rebuild one company you know well: ask for a segment that was recast, as filed and as restated, and click every cell. Ask for every filing in your coverage that mentions a specific supplier and count what comes back. Our guide to checking AI numbers lists the full routine, and the best AI tools for hedge funds and Kepler vs AlphaSense cover the wider field.

Build a company you cover at app.kepler.ai, or book a demo to see it on your own models and definitions.

Frequently asked questions

What is the best Tegus alternative?

For the models and filings work Tegus used to cover, our pick is Kepler. We assemble each company's statements from its own XBRL with every cell cited to the line, read every filing and transcript in full before you ask, and our engineers build your firm's ontology so your definitions, models and notes sit in the same answers. Agents refresh your numbers when a company files, with every change cited.

Is Tegus still around?

Tegus is part of AlphaSense, which agreed to buy it in June 2024 and completed the deal that July. Tegus.com now sends visitors to AlphaSense, where the transcript library is sold as Tegus Expert Insights (300,000+ expert transcripts), live calls as Tegus Expert Call Services, and more than 4,000 Canalyst models sit in the financial data module. BamSEC still runs at bamsec.com as part of AlphaSense.

What are the best alternatives for Tegus expert-call transcripts?

Guidepoint (130,000+ transcripts covering 80,000+ companies, with 7,000 added each month), Third Bridge (100,000+ transcripts, reachable from AI assistants through its MCP server), AlphaSights (its AlphaNow library adds hundreds of transcripts and company one-pagers each week) and In Practise (long-form interviews with former executives, customers, competitors and suppliers of public companies).

What can replace Canalyst models?

Canalyst models are still sold inside AlphaSense. If you'd rather not work inside a pre-built model structure, Kepler builds statements from each filer's XBRL as filed or as restated, adds the KPIs companies report in MD&A tables, footnotes and decks with each cell cited, and applies your firm's definitions. Daloopa supplies source-linked data points on 6,000+ companies for your own templates.

How much does BamSEC cost?

BamSEC lists BamSEC Pro at $69 a month billed annually, with an enterprise plan for teams sold through AlphaSense. Pro covers full-text search across filings and transcripts, table downloads to Excel, filing comparison and alerts. AlphaSense itself doesn't publish prices; SpendHound reports average AlphaSense spend of $10,131 a year for smaller customers and $139,455 for enterprise customers.