Private LLM Stack for Law Firms
A practical private LLM architecture for law firms that need AI assistance without spraying privileged material into unmanaged tools.
A private LLM stack for a law firm should protect privileged material while giving lawyers the chat and document workflows they already expect. The goal is not to ban AI. The goal is to stop client and matter data from leaking into tools the firm cannot govern.
The minimum viable architecture
| Layer | Purpose | Example options |
|---|---|---|
| Chat interface | Lawyer-facing assistant | Open WebUI, LM Studio, Jan |
| Model runtime | Runs approved models | Ollama, vLLM, llama.cpp |
| RAG/document layer | Matter-aware document Q&A | AnythingLLM, Haystack, LlamaIndex |
| Vector database | Stores document embeddings | Qdrant, Weaviate |
| Gateway | Routes requests and logs usage | LiteLLM, internal proxy |
| Identity/access | Keeps matters separated | SSO, groups, matter-level permissions |
| Deployment partner | Makes it usable and supportable | Legal/private AI implementation shop |
Why law firms are different
Law firms have three hard constraints:
- Privilege: client material cannot casually enter unmanaged third-party tools.
- Matter separation: one client’s corpus cannot leak into another client’s workflow.
- Auditability: leadership needs to know what tools received what kind of material.
Consumer AI tools were not designed around those constraints.
Start with three workflows
Do not start by indexing the entire document management system.
Start with:
- internal policy Q&A
- public-law research support
- one controlled matter-document workflow
The first win should prove that lawyers will use the interface and that IT can explain the data boundary.
What to block first
The first policy move is not “no AI.” It is:
- no privileged material in personal AI accounts
- no matter documents in unmanaged browser extensions
- no client records in unapproved chat tools
- no confidential material in image/video AI tools
Then give people a local/private path that does not feel worse.
Vendor questions
Ask every vendor or partner:
- Can matter access be separated?
- Where are documents stored?
- Where are embeddings stored?
- Can logs be exported?
- Can models be restricted?
- Can the system run on-prem or in a private environment?
- What is the offboarding process?
- Who handles updates and support?
Bottom line
The best law-firm AI stack is boring from a security perspective and useful from a lawyer perspective. If it is secure but painful, lawyers will dodge it. If it is easy but unmanaged, risk moves faster than policy.
Run the AI egress audit before choosing tools.