Hebbia
4.4
Hebbia builds research AI for investing, banking, legal and corporate work. Max acts as a research analyst over a document set, and Matrix runs the same question across many companies or documents at once, returning a grid. It connects to filings, earnings transcripts, FactSet, Capital IQ, PitchBook and cloud storage. Pricing is quoted.
- Commercial use OK
- Enterprise contract
- Pricing
- Contact sales
- Free tier
- No
- Commercial use
- Permitted
- Japanese UI
- Not confirmed
- Enterprise contract
- Available
What it is good for
- Diligence across a long list of companies
- Reading filings and transcripts at volume
- Legal and consulting teams working through data rooms
- Analysis that has to be repeated across many documents
Strengths and trade-offs
Strengths
- Matrix turns one question into a structured answer across many sources
- Connects to the market data tools analysts already pay for
- Outputs are traceable to the source document
- Used by named large financial institutions
Trade-offs
- Quoted pricing and enterprise sales cycle
- Aimed at financial and professional services — poor fit elsewhere
- Requires the underlying data subscriptions to be useful
Editors' review
The grid is the product
Most research AI answers one question about one document. Matrix answers one question about two hundred, and that difference is what a diligence team actually needs.
The dependency on existing data subscriptions is worth noting in a budget: Hebbia is a layer over tools you already pay for, not a replacement for them.
Verdict
A strong fit for diligence-heavy work. Irrelevant outside it.
Compiled from official documentation and public sources, with our own editorial judgement. We do not publish figures we cannot source.