AI for Law Firms
Private RAG for contract review and legal research, with client data kept in house.
A short call to see if this is a fit. No pressure, no slides.
Use cases
Contract review support
An agent reads a contract, finds the clauses you flag for, and writes a summary with citations to the exact passages. A lawyer reviews the findings instead of reading every line cold.
Legal research over your own files
An agent searches your matter files and memos, then answers with citations to the source documents, so associates start from what the firm already knows.
Document intake and summaries
Discovery and intake documents get read, summarized, and tagged, so the team sees what matters first.
Precedent and clause retrieval
An agent surfaces the firm's prior clauses and precedents that fit the current matter, with a link to the original.
Where AI fits in a law firm
The fit is narrow and real: reading documents and searching the firm’s own knowledge. An agent that does RAG, retrieval augmented generation, can read a contract or a file and answer with citations to the source.
This is a defensible niche because most firms cannot send client data to a public model. That constraint rules out the easy hosted tools and rewards a careful private build.
Keeping client data in house
We run open-weight models on hardware the firm controls and use private RAG so answers stay grounded in your own documents, with a citation for every claim. When the system reaches other tools, standards like the Model Context Protocol keep the wiring tidy and auditable.
Built carefully, with a human responsible
AI output here is a first pass. Every answer shows its source, and a lawyer verifies before it becomes work product. We design the workflow so responsibility stays with a person, which is where the rules and the ethics put it.
How we deliver
Start with a short readiness audit to confirm the fit and pick the first use case. From there it is usually a private RAG build over a defined set of documents.
Honest cost note
Private RAG costs more than a hosted tool, and it is the right call for client data. But if a task touches no confidential data, a cheaper hosted option may be fine, and we will tell you when that is true.
FAQ
See the questions above on client data and trusting the output.
Frequently asked questions
Will client data go to OpenAI or another public model?
No, not in this design. We run open-weight models on hardware the firm controls, so client data stays in house. That is the whole reason private RAG fits a law firm.
Can I trust the output for legal work?
Treat it as a fast first pass, not a final answer. Every output shows its source so a lawyer can verify. The model can misread a passage, so a human stays responsible for the work product. We design the workflow around that.
Solutions for this industry
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See if AI fits your team
A short call to see if this is a fit. No pressure, no slides.
Book a scoping call