Hebbia
Editor's pickAI document analysis at deal scale — the Matrix platform for finance
4.6Enterprise / CustomBest for Funds running document-heavy diligence who want auditable AI analysis
AI Diligence Document Analysis
Overview
Hebbia's Matrix platform runs AI analysis across thousands of documents at once in a grid interface — rows of documents, columns of questions — built for the diligence-heavy workflows of asset managers, banks, and law firms. It raised a $130M Series B led by Andreessen Horowitz in 2024, and venture teams use it to tear through data rooms, LPAs, market studies, and stacks of decks with citations back to source.
Key features
- Matrix grid: run structured questions across thousands of documents
- Citations back to exact source passages
- Handles PDFs, decks, spreadsheets, and data-room exports
- Reusable analysis templates for repeatable diligence
- Enterprise security and private deployment options
Pros
- Genuinely built for multi-document finance workflows, not chat-with-PDF
- Auditable outputs — every cell traces to a source
- Strong adoption among sophisticated institutional investors
Cons
- Enterprise pricing beyond most sub-scale funds
- Requires workflow thought to get past ad hoc usage
- Overkill if your diligence is a handful of documents per deal