Hebbia

AI analysis platform for complex financial and legal documents.

Hebbia is an AI analysis platform designed for financial and legal professionals who need to extract answers and insights from large volumes of complex, unstructured documents. Rather than simple document search, Hebbia enables users to pose multi-step analytical questions across entire document sets — data rooms, fund documents, legal contracts, filings — and receive structured, cited answers. It is positioned for enterprise use cases where the document corpus is large and the analysis requirements are sophisticated, such as investment due diligence, fund analysis, and legal review. Hebbia differentiates itself by focusing on analytical depth and accuracy across large document sets, with on-premise deployment available for clients with strict data confidentiality requirements. Notable customers include Centerview Partners and Charlesbank.

Compliance

ISO 27001 SOC 2

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Key Features

Multi-step document analysis: Enables users to ask complex, multi-part analytical questions across large document collections and receive structured answers, going beyond keyword search to genuine analytical synthesis.
Large-scale document processing: Handles entire data rooms, fund document libraries, or contract portfolios in a single workspace, rather than requiring users to analyze documents one at a time.
Cited outputs: Answers are grounded in and linked back to source documents, allowing professionals to verify claims and maintain the audit trail that financial and legal work requires.
Structured output generation: Can produce structured tables, summaries, and comparisons across documents — useful for side-by-side analysis of fund terms, contract provisions, or company financials.
On-premise deployment: Offers on-premise deployment for clients who cannot send confidential financial or legal documents to a third-party cloud environment.
Multi-model support: Uses multiple underlying LLMs, allowing the platform to balance capability, context length, and cost across different document analysis tasks.

Use Cases

For investment professionals conducting due diligence: A private equity or investment banking team reviewing a data room with hundreds of documents uses Hebbia to run analytical queries across the entire corpus, extracting key terms, risks, and financial data points in a fraction of the time manual review would require.
For fund-of-funds teams analyzing LP documents: A fund-of-funds team managing a large portfolio uses Hebbia to process and compare fund documents across their holdings, extracting fee structures, terms, and performance data at scale.
For legal teams reviewing large contract portfolios: A legal team conducting a contract review — during M&A diligence or a regulatory audit — uses Hebbia to identify relevant clauses and obligations across hundreds of agreements simultaneously.

Pricing MODELS

Enterprise

Pricing Summary

Hebbia uses a custom enterprise pricing model. No self-serve tiers or publicly listed prices are available — organizations engage with the company directly for pricing.