Analyze documents
Summarize information, compare files, and identify key findings.
An AI research tool for finance and legal teams that answers questions across hundreds of documents at once, with citations.
Hebbia is an AI research tool for document-heavy finance, legal, and consulting work. Its core product, Max, lets an analyst ask a question across large sets of documents at once, such as hundreds of contracts, filings, or earnings transcripts, and get answers with citations back to the source. Investment banks, asset managers, and law firms use it; customers include Morgan Stanley and Centerview Partners. It connects to SEC filings, FactSet, S&P Capital IQ, PitchBook, and Preqin, and to internal file storage like SharePoint, OneDrive, Box, and Dropbox. Hebbia states it does not train models on customer data and keeps each client's data isolated. It holds SOC 2 Type II and ISO/IEC 42001 certifications and supports US and EU processing regions.
This fits an investment firm, law firm, or consulting practice whose core job is reading dense documents, such as due diligence, credit analysis, or contract review, especially where junior staff now search filings, transcripts, and contracts by hand. A sensible starting point is a pilot with one analyst team on one workflow, like diligence document review, using your own document set rather than a generic demo. Hebbia does not publish pricing, so treat any figure as a placeholder and get a quote tied to your seat count and data sources. Because it is built for specialized, document-heavy work, it may be more than a team needs if its main need is simple everyday company search.
Potential matches to review against your requirements. Explore matching tools or read a task guide before you choose.
Summarize information, compare files, and identify key findings.
Turn approved content and customer requirements into proposal drafts for your sales team.
Find answers across your documents and internal resources.
Identify bottlenecks and support frontline teams with clearer work instructions and operational insights.
Find relevant answers, route requests, and help service teams respond to customers sooner.
Analyze spending, compare suppliers, and identify opportunities to improve purchasing.
Explore external sources to support business decisions.
The industries and leadership roles this tool is most often matched with.
How one company factor at a time moves the modeled score. The published score is unchanged.
These estimates cover licensing, setup, integrations, staff time, security, administration, and support.
| Cost measure | Low | Base | High |
|---|---|---|---|
| First-year total | $18.7K | $30.5K | $50.6K |
| Three-year total | $34.5K | $54.1K | $87.3K |
| First-year cost per unit | $935 | $1.5K | $2.5K |
| Average annual cost per unit (over three years) | $574 | $902 | $1.5K |
| Component | Low | Base | High |
|---|---|---|---|
| Licensing and usage | $975 | $1.3K | $1.8K |
| Implementation | $5.1K | $8.5K | $14.5K |
| Integration | $3.6K | $6.5K | $11.7K |
| Staff time and change management | $2.9K | $4.2K | $5.9K |
| Security | $2.5K | $3.5K | $5.3K |
| Administration | $1.9K | $2.5K | $3.4K |
| Support | $900 | $1.2K | $1.6K |
Estimate assumptions: This scenario uses a category-based allowance, not a verified price for this product. Based on 20 enabled users. Confirm the vendor’s billing unit and current price or quote before budgeting.
Benefits have not been estimated: The current research does not estimate potential savings, return on investment, or how long it would take to recover the cost. Earlier benefit estimates are excluded.
Confirm current product identity, commercial packaging, data processing terms, sign-in and access rules, retention, integrations, support model, implementation effort, and rollback conditions.
Verify identity, package, availability, ownership, pricing, and security evidence before approving a pilot
Do not approve a pilot yet. Verify the current product identity, package, availability, owner, pricing, and security evidence; then define one workflow, a baseline, and rollback criteria.
Define what success looks like for a test of Hebbia and assign someone to lead it.
Once the requirements above are met, compare a small trial with how your team works today.
Track adoption, output quality, business results, and actual costs against the estimate.
Use the results to decide whether to stop, adjust, or expand the pilot.
Confirm encryption, how the vendor uses your data, customer data separation, how long data stays and how to delete it, activity records, sign-in and user setup, where data is handled, other companies that process data, past incidents, and what your team must manage.
Keep source documents in the data room or repository and export Hebbia projects, matrices, questions, citations, annotations, outputs, and reviewer corrections. Matrix logic and retrieval behavior may not transfer directly, so preserve the workpaper and retest representative analyses on a replacement.
Do not approve a pilot yet. Verify the current product identity, package, availability, owner, pricing, and security evidence; then define one workflow, a baseline, and rollback criteria.
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Where to check the product, price, security, and support.
Research observations recorded: 1. Evidence quality: Good support.
Recorded score and category rank across research updates.
Answer a few questions about your company and compare this tool with others. The research score above stays the same.
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