HHebbia

Hebbia’s annual recurring revenue reached $50 million in September 2026, nearly four times the $13 million it reported in June 2024, and its CEO called the third quarter the biggest in the company’s history. The platform’s Matrix agents read data rooms, filings, transcripts and models at scale and return cited answers, buyer profiles and draft CIMs for investment banks and investors.

It is best for deal teams that live in documents: bankers building CIMs and buyer lists, and investors running diligence. Points to weigh are enterprise pricing shared by quote, which some reviewers find expensive, a learning curve, and outputs that benefit from careful review. We rate it 8.0/10 on our scale. We have not used Hebbia; this review is based on Hebbia’s own pages and blog, Wikipedia’s company history, ARR Club’s report on its growth and public G2 reviews.

Funding History and Milestones Shared by Hebbia’s CEO

Hebbia has more public financial detail than most finance AI vendors, thanks to its funding history and a CEO who shares growth milestones.

Retention matters more than the headline ARR for a buyer. Gross revenue retention above 95% suggests firms that adopt Hebbia mostly keep paying for it, which is a fair proxy for whether the product earns its place in daily deal work. The fivefold rise in daily active users in one quarter also points to use spreading inside firms, beyond new customers.

The investor list helps with procurement. Backing from Andreessen Horowitz, Index Ventures and GV and more than $160 million raised by 2024 make Hebbia less likely to vanish mid-contract than a seed-stage tool, which matters when you are loading years of deal files into it.

The product moves have followed the money. The 2025 FlashDocs deal took Hebbia from reading documents to writing them, with decks, memos and CIMs generated inside the platform. The 2026 API and MCP server push it toward being infrastructure that other tools call, rather than one more window a banker has to open.

Matrix, Chat, Deep Research and the New Max

Hebbia offers several ways in: Matrix for structured analysis, Chat for quick questions, Deep Research for broad investigations and, since 2026, Max, which it describes as an AI teammate.

Matrix

Matrix is a grid. Rows are documents, such as a data room, a set of filings or a batch of transcripts; columns are questions. Hebbia’s agents work through every cell, extracting answers and linking each one to its source. Hebbia says its Iterative Source Decomposition approach keeps document structure and formatting intact rather than chopping files into fragments for retrieval. Matrix 2.0, launched in 2026, adds what Hebbia calls next-generation research and analysis agents.

Banking Workflows

• CIM creation: turns data room materials and management call notes into a CIM draft in days rather than weeks, according to Hebbia.
• Strip profiles: pulls management, positioning and M&A history from sources such as PitchBook and CapIQ, with sourcing built in.
• Pitch books: gathers KPIs, market sizing and competitive intelligence, builds market maps and keeps a searchable base of prior pitch content.
• Buyer profiles: uses Deep Research to review deal history, portfolio companies and acquisition strategy across public, private, web and internal sources.
• Model inputs: links assumptions in financial models to filings, call notes and CIMs and tracks changes across versions.
• Diligence Q&A: drafts likely diligence questions and source-backed answers.

Connections

Hebbia lists partnerships with Databricks, the data room provider Datasite and credit research firm Octus, and its workflows draw on PitchBook and CapIQ. The 2026 API and MCP server let firms bring Hebbia into tools they already use. OpenAI announced in 2025 that its models were integrated into Matrix.

Max, Chat and Deep Research

Not every task needs a grid. Chat answers quick questions against a set of documents, and Deep Research runs broad investigations, such as profiling every likely acquirer of a target, across public filings, private data, the web and a firm’s own files. Max, launched in the third quarter of 2026, is pitched as an AI teammate that works across these tools. Together they let one platform cover both the quick lookup and the multi-day diligence project.

Bankers Still Judge Valuation and Edit Client Drafts

Bankers decide what to ask, check the cited sources and edit drafts before anything reaches a client. Hebbia shortens the reading and first-draft work; judgment on valuation, positioning and negotiation stays with the deal team. Reviewers also note that complex multi-step workflows take time to learn.

A Demo Page in Place of Published Prices

Hebbia does not publish prices. Its pricing page routes buyers to a demo and links to its security page, data processing agreement and terms.

Judging a Quote by Hours Saved on CIMs and Diligence

Without public prices, the best way to judge a Hebbia quote is against the time it saves. These scenarios use Hebbia’s own workflow claims; team sizes and hours are our illustrations.

• A five-banker deal team: if Hebbia cuts a CIM first draft from weeks to days, as it claims, the saving is measured in analyst weeks per mandate. Price the license against the fully loaded cost of those weeks across your annual deal count.
• A diligence-heavy investor: Deep Research reading up to 350 sources in one run replaces hours of manual screening per target. Count targets screened per year to size the value.
• A firm comparing quotes: Rogo also sells by quote only, so run both on the same live mandate and compare cost per seat alongside output quality.

Other costs to plan for: usage limits that reviewers mention, time to set up templates and train staff, and data source subscriptions such as PitchBook or CapIQ that Hebbia draws on but does not replace.

Hebbia Compared With Rogo, AlphaSense, Perplexity Deep Research and Harvey

Finance research agents range from banking-specific platforms to general research tools. Hebbia sits between the two, with banking workflows and a broader base in investing and law.

Hebbia and Rogo are the two to shortlist for a bank. Choose Hebbia for document-heavy diligence across many file types and for firms that also work with legal teams; choose Rogo if you want a tool shaped tightly around banker workflows. Perplexity is a low-cost supplement, not a substitute, for confidential deal work. AlphaSense, with far more G2 reviews, is the better pick when the job is tracking markets and expert calls rather than drafting deal materials from a data room. See more in our AI agents for banking and research agents guides.

Investment Bankers, PE Firms and Credit Investors

• Investment banking teams: CIM drafts, strip profiles, buyer lists and diligence Q&A are documented workflows.
• Private equity and credit investors: Matrix suits screening data rooms and comparing terms across many documents, and Octus and Datasite partnerships fit credit and deal work.
• Asset managers with large research libraries: cited answers across filings and transcripts speed up coverage work.
• Firms that need traceable answers: every Matrix answer links to its source, which helps compliance and review.
• Firms building their own tools: the API and MCP server let engineering teams bring Hebbia into internal systems.

Retail Bank Operations and Small Firms Wanting Simplicity

• Retail and commercial bank operations: Hebbia does not handle customer service, onboarding or loan processing; look at agents built for those jobs.
• Small firms that need a known price: there is no public pricing, and some reviewers find it expensive.
• Teams that want a simple chat tool: Matrix workflows take time to learn.
• Users who mainly need open web research: Perplexity Deep Research costs far less.
• Firms that prefer not to review AI output: drafts and extractions still need checking before they reach clients.

Quote-Based Pricing and the Learning Curve

• Pricing detail: ask for seat and usage pricing in writing, including what happens when usage limits are hit.
• Learning curve: budget training time; reviewers say complex workflows take practice.
• Uploads and file handling: G2 reviewers mention file management and upload issues, so test with your own data room formats.
• Confidential data: review Hebbia’s security page and data processing agreement before loading client files, and confirm how model providers handle your data.
• Overlap with data vendors: Hebbia draws on PitchBook, CapIQ and similar sources, so it adds a layer on top of those subscriptions rather than replacing them.
• Company figures: ARR, retention and user growth come from Hebbia’s CEO, reported by ARR Club.

Max and Matrix 2.0 Launch as New ARR Triples

• On October 22, 2026, ARR Club reported that Hebbia tripled new ARR in Q3 2026, passed $50 million in ARR and launched Max, Matrix 2.0 and an API and MCP server.
• On July 10, 2025, Hebbia outlined six investment banking workflows, including CIM drafting and buyer profiles, after integrating FlashDocs.

A Leading Choice for Finance Teams Living in Documents

For banks, private equity firms and asset managers that spend their days in documents, Hebbia is one of the strongest options available. It scores 8.0/10 on our scale: strong on integrations and user sentiment, solid on autonomy for multi-step document analysis, with room to grow on pricing value, since prices are shared by quote and some reviewers find it expensive. Growth to $50 million in ARR with retention above 95% suggests firms that buy it keep using it.

Before signing, run Hebbia and Rogo side by side on a live mandate, with your own data room files, and measure time saved on the CIM, buyer list and diligence answers. Get usage limits and seat pricing in writing, and confirm how confidential documents are handled. If the time saved covers the license on a handful of mandates a year, it is likely worth it.

Firms outside capital markets should be clear about fit. A regional or community bank looking to automate member service, onboarding or lending will likely be better served by agents built for those jobs; Hebbia’s value shows up where analysts spend hours reading and summarizing documents for deals and investments.

Matrix, CIM Drafting and the Rogo Comparison

How Much Does Hebbia Cost?

Hebbia does not publish prices. It sells enterprise contracts after a demo, and G2 reviewers describe pricing as expensive and not transparent.

What Is Hebbia Matrix?

Matrix is Hebbia’s main product: a grid that runs questions across many documents at once and returns answers linked to their sources. Matrix 2.0, launched in 2026, adds new research and analysis agents.

Can Hebbia Draft a CIM or Pitch Book?

Hebbia says Matrix can turn data room materials and management call notes into a CIM draft, and its FlashDocs acquisition lets users generate decks and memos inside the platform. Bankers still edit and approve the output.

Is Hebbia Better Than Rogo for Investment Banks?

Both target banks and sell by quote. Hebbia is broader across banking, investing and law with strong document analysis, while Rogo is shaped more tightly around investment banking workflows. Testing both on a live deal is the best way to decide.

Is Hebbia Safe for Confidential Deal Documents?

Hebbia publishes a security page and a data processing agreement and serves investment banks and law firms. Firms should review those documents and confirm data handling with Hebbia before uploading client files.