Hebbia

Hebbia is an enterprise AI platform that analyzes financial and legal documents at scale, helping investors, bankers, and advisors extract insights from large, complex datasets.

Hebbia is an American AI company building automation and knowledge tools for financial and legal research. Its flagship product, Matrix, lets users extract and reason over information from documents of any format, including contracts, presentations, spreadsheets, transcripts, and SEC filings, using natural language. The platform is purpose-built for institutional finance, supporting M&A diligence, credit agreement analysis, contract review, market research synthesis, and investment memo generation. Hebbia emphasizes analytical scale (reasoning over very large context), enterprise collaboration with shared context across teams, and automated workflows that encode and continuously run firm processes. It integrates with private documents, public filings, and data providers such as FactSet, S&P Capital IQ, PitchBook, Snowflake, SharePoint, and Box, and meets enterprise security standards (SOC 2 Type II, ISO/IEC 42001). Founded in 2020 by former Stanford PhD student George Sivulka, Hebbia is headquartered in New York and counts KKR, Morgan Stanley, MetLife, Centerview Partners, and law firm Latham & Watkins among its customers. In 2025 it acquired FlashDocs to add generative slide-deck and artifact generation.

Category

Enterprise Search & Knowledge

Pricing

custom, seat-based, annual contract

Target Market

Enterprise, Investment Banking, Private Equity, Asset Management, Legal / Law Firms, Corporate Finance, Professional Services

Founded

2020

Headquarters

New York City, New York, USA

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  Matrix document analysis

  Extracts and reasons over information across PDFs, spreadsheets, transcripts, filings, and contracts using natural-language queries.

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  Large-scale context reasoning

  Analyzes vast document sets and limitless context to surface insights that would be impractical to find manually.

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  Automated workflows

  Encodes recurring firm processes (e.g., diligence checklists, investment memos) and runs them continuously across new data.

• ✓
  Enterprise integrations and data providers

  Connects to private documents and external sources including FactSet, S&P Capital IQ, PitchBook, Snowflake, SharePoint, and Box.

• ✓
  Enterprise-grade security

  SOC 2 Type II, ISO/IEC 42001:2023 compliance, and end-to-end encryption for sensitive financial and legal data.

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  M&A and credit due diligence

  Analyze deal documents and credit agreements to identify negotiation leverage, risks, and key terms across large data rooms.

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  Investment research and memo generation

  Synthesize market research, filings, and earnings transcripts and auto-generate investment memos, diligence reports, and board decks.

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  Legal contract and filing review

  Summarize and extract terms from customer contracts, filings, and legal documents for law firms and corporate legal teams.

Pricing is not public; Hebbia uses a seat-based enterprise model with unlimited usage within seat tiers and an enterprise sales process. Third-party estimates compare per-seat cost to a Bloomberg Terminal (potentially upwards of ~$20,000/user/year); not officially confirmed.

This page was written from 5 sources, 4 on domains other than hebbia.com.

1. 1.hebbia.com — hebbia.comvendor
2. 2.en.wikipedia.org — Hebbia
3. 3.crunchbase.com — hebbia
4. 4.g2.com — reviews
5. 5.research.contrary.com — hebbia