Hebbia

Hebbia is an AI research platform for investors, bankers, lawyers and consultants that reads large sets of documents and market data and turns them into tables, memos and decks. Rather than a single chat box, its signature Matrix view lays documents out as rows and questions as columns, so AI agents fill in a grid of cited answers across hundreds or thousands of files. That structure suits due diligence and comparison work where every cell needs to be checked.

What is Hebbia used for?

Hebbia is used for research jobs that would normally take junior analysts days of reading.

• Running due diligence across a data room, extracting key terms and risks from every document
• Comparing companies on financials, growth, valuation, leverage and credit ratings
• Reviewing SEC filings, earnings call transcripts and international company filings
• Pulling market data from FactSet, S&P Capital IQ, PitchBook, Preqin and Fitch alongside internal files
• Drafting opportunity snapshots, memos and PowerPoint materials for deal teams
• Sharing AI work across a deal team instead of keeping it in one person's chat history

Who Hebbia is best for

Hebbia is designed for private equity and hedge funds, investment banks, asset managers, law firms, consultancies and corporate development teams at large companies. It suits groups that already pay for professional data feeds and manage big document sets. Individual investors, small businesses and anyone looking for a self-serve tool should look elsewhere, since Hebbia sells to institutions.

Hebbia pricing

As of October 2026, Hebbia does not publish pricing. Access is sold to organizations through a sales process that starts with a demo request on its website. Expect pricing to depend on the number of users, the data sources and integrations you need, and your security requirements. Ask for a scoped quote and details on data handling during the demo.

Limitations to keep in mind

• No public pricing, free plan or individual sign-up
• Access to third-party data such as FactSet or PitchBook may depend on licenses your firm holds, so confirm this during evaluation
• AI extraction across many documents still needs review before it goes into a client deliverable

Hebbia vs alternatives

AlphaSense is the better choice when market intelligence, expert call transcripts and broker research are the core need, and it is widely used by corporate strategy teams. Fiscal.ai is more accessible for public equity research, with company financials and AI analysis for individual investors and smaller funds. Glean is an enterprise search assistant across workplace apps rather than a finance research tool. ChatGPT can handle ad hoc document questions but lacks Hebbia's grid workflow and finance data connectors. Hebbia wins for structured, high-volume document analysis inside deal teams.

Tips for getting started with Hebbia

Bring a real past deal or data room to the demo so you can compare Hebbia's Matrix output with work your team has already checked. Define your columns as precise questions, such as change of control clauses or revenue concentration, rather than broad prompts. Agree on a review process for AI-filled cells before using outputs in client materials.

Hebbia FAQ

Is Hebbia free?

No. Hebbia is an enterprise platform with no free plan, and pricing is provided after a demo request.

What is Hebbia Matrix?

Matrix is Hebbia's grid interface where documents form the rows and questions form the columns, letting AI agents extract and compare cited answers across many files at once.

Who uses Hebbia?

Hebbia is used by investors, investment bankers, lawyers, consultants and corporate teams that research large volumes of documents and financial data.

What is the best alternative to Hebbia?

AlphaSense is the strongest alternative for market intelligence, while Fiscal.ai suits public equity research for smaller teams.