Harvey vs Hebbia
A side-by-side comparison of Harvey and Hebbia, drawn from Ignaite's continuously-verified listings.
Compared from listings verified as of
At a glance
| Attribute | Harvey | Hebbia |
|---|---|---|
| Category (differs) | Legal | Finance |
| Pricing | PAID | PAID |
| License | Proprietary | Proprietary |
| Deployment | Cloud | Cloud |
| Platforms | Web | Web |
| Model support | Multi-model | Multi-model |
| Vendor (differs) | Harvey AI | Hebbia |
| Capabilities (differs) |
|
|
The honest brief
Harvey
The default general-purpose legal AI at scale: Vault analyzes up to ~100K-doc collections, used across AmLaw 100 firms.
- Adopted by most AmLaw 100 firms
- Bulk doc analysis via Vault
- Grounds answers in firm's own materials
- Operates across 60 countries
- No public pricing, sales-only
- ~$1,000+/lawyer/mo, 20-seat minimum
- Tuned to big-firm billable workflows
- Heavy enterprise onboarding
Hebbia
Matrix answers each query as a traceable spreadsheet grid via an agent swarm over millions of docs, not one RAG pass.
- Spreadsheet-grid answers across docs
- Citation-first, source traceability
- Handles millions of documents
- SOC 2 / ISO 27001, no data training
- No public pricing, sales-only
- Heavy enterprise onboarding
- Overbuilt for small teams
- Answers a fixed doc set, takes no actions
When to pick which
Both cover Chat with documents.
Pick Harvey if you need Legal research, Contract review, and Contract drafting.
- Legal research (primary capability)
- Contract review (secondary capability)
- Contract drafting (secondary capability)
Pick Hebbia if you need Trigger-action automation, Cited answers, Structured extraction, and Financial research.
- Trigger-action automation (secondary capability)
- Cited answers (primary capability)
- Structured extraction (secondary capability)
- Financial research (secondary capability)
Hebbia leans on Chat with documents as a headline capability; Harvey treats it as secondary.
- Chat with documents (primary capability)