Rogo vs Hebbia in 2026
8 min read
Muhammad AliFounder, consultance.ai
Rogo and Hebbia are both enterprise AI platforms for finance with agents that produce models, decks and memos. Rogo is concentrated in investment banking and built around delegating work to its Felix agent, while Hebbia centers on Matrix, grid style analysis over large document sets with citations, plus its Max agent. Neither publishes list pricing, so a pilot on your own live work is the way to decide.
The shortlist
- Rogo's homepage claims 50,000+ bankers and investors at 350+ institutions; named users include Lazard, Moelis, Jefferies and Nomura.
- Hebbia's about page states $30T in AUM across firms using it and 1,000+ use cases in production.
- Rogo raised a $160M Series D in April 2026 led by Kleiner Perkins, taking total funding past $300M.
- Hebbia's most recent confirmed round in our sources is a $130M Series B in July 2024 led by Andreessen Horowitz.
- Neither vendor publishes list pricing; both route buyers to a demo.
- Hebbia added an Excel plug-in, Excel cell citations and ICE fixed income data in its July 2026 update.
Rogo and Hebbia are both enterprise AI platforms built for finance, and the honest short answer is that Rogo leans toward investment banking workflows run by an agent you delegate to, while Hebbia leans toward document-scale analysis through its Matrix grid with traceable citations. Both now sell an agent that produces decks, models and memos, so the real decision comes down to which workflows your team runs most, which data sources you already pay for, and how you want to buy.
This comparison uses only what each company publishes on its own site plus independent reporting, all fetched on October 1, 2026. Where something is not public, we say so.
Rogo vs Hebbia at a glance
| Rogo | Hebbia | |
|---|---|---|
| Positioning | "AI for the most ambitious firms in finance" | "AI built for the rigor of finance" |
| Flagship agent | Felix, delegated by email "like you would a colleague" | Max, described as an "always-on analyst" |
| Document analysis | Agents across deals and investments, embedded in firm systems | Matrix, analysis over large document sets with traceability to each finding |
| Stated outputs | Excel models, investment memos, diligence materials, slide decks | PowerPoint, Excel models, structured matrices, reports |
| Published scale | 50,000+ bankers and investors, 350+ institutions, 150,000+ daily queries | $30T AUM of firms using it, 1,000+ use cases in production |
| Named users | Rothschild & Co, Jefferies, Lazard, Moelis, Nomura, Truist Securities, Baird | Centerview Partners, Charlesbank, Fenwick, Apogem Capital, Provident Healthcare Partners |
| Latest announced round | $160M Series D, April 2026, led by Kleiner Perkins | $130M Series B, July 2024, led by Andreessen Horowitz |
| Security listed on site | SOC 2, ISO 27001, GDPR, CCPA, EU AI Act | SOC 2 Type 2, ISO/IEC 27001:2022, ISO/IEC 42001:2023, GDPR, CCPA |
| List pricing | Not published | Not published |
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Rogo
Rogo describes itself as "the trusted AI partner to the world's leading financial institutions." It was founded in 2022 by Gabriel Stengel, John Willett and Tumas Rackaitis, according to Tech Funding News and Contrary Research. Its homepage says the team is made up of former bankers and investors and that the platform and model are "built explicitly for finance."
The product centers on agents. Rogo says its agents "execute end-to-end work across deals and investments," and that the platform produces "auditable Excel models, investment memos, diligence materials, and slide decks." Its agent, Felix, is pitched as something you delegate to rather than search with. The Felix page says you can "email Felix like you would a colleague," and lists three kinds of work: decks ("Shell the deck. Refresh the materials. Turn the comments."), spreadsheets ("Build the model. Spread the comps. Update the backup.") and reports ("Draft the memo. Prep the meeting. Run the research."). The Series D press release describes Felix handling deal screening, CIM generation, buyer outreach and data room diligence.
On integrations, Rogo says it is embedded "from SharePoint and CRM to the financial data platforms your team relies on." Contrary Research lists connections to Capital IQ, Preqin, PitchBook, Crunchbase, London Stock Exchange Group and Dow Jones Newswires, and reports that Rogo acquired Subset, an AI native spreadsheet startup, in September 2025. Rogo also says that "every Rogo deployment is bespoke," led by former finance professionals acting as change management partners.
On scale, the homepage currently claims more than 50,000 bankers and investors, more than 150,000 daily queries and more than 350 institutions. The April 2026 Series D release gave a smaller figure at that time: more than 35,000 professionals at over 250 institutions, naming Rothschild & Co, Jefferies, Lazard, Moelis and Nomura. Homepage testimonials come from executives at Truist Securities, Nomura and Baird.
Funding is well documented. Rogo raised a $160 million Series D in April 2026 led by Kleiner Perkins, with Sequoia, Thrive Capital, Khosla Ventures and J.P. Morgan Growth Equity Partners among the participants, bringing total funding past $300 million. Contrary Research reports a $75 million Series C in January 2026 led by Sequoia at a $750 million valuation, followed by a first international office in London.
Hebbia
Hebbia calls its offering "Institutional Intelligence" and says it is "trusted by leading investors, bankers, lawyers, consultants, and Fortune 500 companies." TechCrunch reported in 2024 that George Sivulka founded the company in 2020 while working on a PhD at Stanford.
Hebbia sells two named products. Matrix is described on the product page as a way to "reason over any volume of documents or companies with precise analysis and complete traceability back to every finding." TechCrunch described it as a tool that can "ingest multiple files of unlimited length" and answer "in a tabular format, similar to a spreadsheet." Max is its agent, described as an "always-on analyst" that researches deals "to produce client-ready spreadsheets, slides, and reports."
Hebbia's July 2026 product update added an Excel plug-in that runs Hebbia workflows inside spreadsheets, Excel cell citations through Office notes, shareable custom skills, and fixed income pricing data from Intercontinental Exchange. For banks specifically, Hebbia's investment banking page lists CIM drafting, answering buyer questions from VDR data, valuation work, precedent benchmarking and buyer list building.
The data integration list on Hebbia's homepage is long and specific. It names SEC filings, earnings transcripts, European filings, UK Companies House, Australia and NZ filings, FactSet, S&P Capital IQ, PitchBook, Preqin, Fitch, ICE Market Data and EMMA on the market data side. On the firm side it names SharePoint, OneDrive, Box, Dropbox, Egnyte, AWS, Intralinks, Salesforce, DealCloud, Snowflake and Databricks, plus expert network sources Third Bridge and Guidepoint.
On scale, Hebbia's about page states $30 trillion in AUM across firms using it, more than 1,000 use cases in production and five years of deployment at top firms. Its homepage quotes Apogem Capital's CTO saying diligence document review went from 12 hours a day to "an hour or two." The most recent funding round confirmed in sources fetched for this post is the $130 million Series B in July 2024, led by Andreessen Horowitz with Index Ventures, Google Ventures and Peter Thiel. TechCrunch reported a valuation of roughly $700 million and $13 million in revenue at the time, and named Centerview Partners, Charlesbank and Fenwick as customers.
Where they actually differ
On paper the two products have converged. Both now offer an agent that produces Excel models, decks and memos, both connect to the major financial data platforms, and both serve banks and investors. The differences show up in emphasis.
Center of gravity. Rogo's named customers and testimonials are concentrated in investment banking: Lazard, Moelis, Jefferies, Rothschild & Co, Nomura, Baird and Truist Securities. Hebbia's homepage spreads across investing, banking, legal transaction advisory and corporate finance teams, and its 2024 coverage included a law firm among its named customers. If your work is mostly sell side banking, Rogo's references are closer to your desk. If you run diligence across many document types or have legal and investing teams on the same platform, Hebbia's footprint is wider.
How you interact with it. Rogo's Felix is built around delegation, including by email, with work refined over time. Hebbia's Matrix is built around a table that lays out documents or companies against the questions you ask, with traceability back to the source. Max sits on top of that for deliverables. Teams that review hundreds of documents side by side tend to think in grids. Teams that hand a junior a task and wait for the draft tend to think in delegation.
Deployment model. Rogo states that every deployment is bespoke and paired with a former finance practitioner for change management. Hebbia's public pages direct buyers to a demo and do not describe deployment structure in the pages fetched for this post.
Security posture. Both list SOC 2, ISO 27001, GDPR and CCPA. Hebbia additionally lists ISO/IEC 42001:2023, the AI management system standard. Rogo lists the EU AI Act. Ask either vendor for the actual reports rather than relying on badges.
Pricing
Neither company publishes list pricing. Rogo's site and Hebbia's site both route buyers to a demo request. Contrary Research notes Rogo sells per seat subscriptions and cites an unconfirmed estimate, which Rogo does not confirm. A Hebbia blog post on token efficiency carries the heading "Price the workflow, not the token," but states no prices. Treat any per seat figure you see online as an estimate until you have a quote, and expect pricing to depend on seat count, contract length and the data sources included.
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Working systems, the stack behind them, and what they cost to run.
Open the libraryHow to choose between Rogo and Hebbia
Run a two week pilot on your own work, not the vendor's demo deck. Pick three live tasks: one CIM or teaser section, one comps or model update, and one diligence pass over a real data room. Score each tool on whether the output is usable without rework and whether every number traces to a source you can open.
- Choose Rogo if your team is primarily investment banking, you want an agent you delegate to, and you value a vendor that runs a bespoke rollout with former bankers.
- Choose Hebbia if your work is heavy on document volume across many formats, you want grid style analysis with cell level citations, or you need the breadth of its listed data and file integrations, including expert network transcripts.
- Check your existing data contracts. Both connect to premium data platforms, and the value of either depends on licenses you already hold.
Private equity teams weighing either tool for diligence should also read our notes on AI for financial due diligence, and deal teams can see how we approach AI deal desk systems.
The third option: build it and own it
Both Rogo and Hebbia are seat licenses on a shared platform. That is the right answer for many firms. It is less right when your edge sits in a proprietary process, such as your own screening criteria, your IC memo format or your portfolio monitoring logic, and you would rather that logic live in code you control.
That is the work consultance.ai does. We build custom finance AI for funds, banks and family offices, the first system is typically live in about six weeks, and the client owns the code. If you want to compare that path against a vendor seat, book a call or browse the consultance.ai library for the prompts and workflows we use with private equity teams.
Sources
- Rogo homepage, fetched 2026-10-01
- Rogo, Felix product page, fetched 2026-10-01
- PR Newswire, Rogo Raises $160M Series D, fetched 2026-10-01
- Tech Funding News, Kleiner Perkins leads Rogo's $160M raise, fetched 2026-10-01
- Contrary Research, Rogo business breakdown, fetched 2026-10-01
- Hebbia homepage, fetched 2026-10-01
- Hebbia, product page, fetched 2026-10-01
- Hebbia, about page, fetched 2026-10-01
- Hebbia, investment banking page, fetched 2026-10-01
- Hebbia, What's New: July Disclosure 2026, fetched 2026-10-01
- Hebbia, Series B announcement, fetched 2026-10-01
- Hebbia, How Hebbia Approaches Token Efficiency for Financial AI, fetched 2026-10-01
- TechCrunch, Hebbia raised $130M at a $700M valuation, fetched 2026-10-01
Finance AI, built to hold up under review
Finance AI should survivethe investment committee,not just the demo.