Sector
AI consultancy for legal and professional services
Privilege and confidentiality make hosted AI a short conversation with your risk partner. Private retrieval over your own matter files keeps it inside the firm.
The constraint
Why law firms stall on AI
The material that would make AI valuable (matter files, advice, correspondence, precedent) is privileged, confidential and often under client restrictions on where it may be processed.
Most risk partners end the third-party API conversation quickly, and reasonably. Vendor trust is beside the point. Can the firm characterise and control the processing well enough to meet its duties to clients who never consented to it?
Meanwhile clients ask what the firm is doing with AI, increasingly in tenders. Doing nothing is now a competitive position.
Where it works
Where AI earns its place
Ordered roughly by how quickly they get approved. The first is usually the right first project: it is the least contentious.
Precedent and know-how retrieval
Find the firm’s own clauses, advice and arguments, cited to source. Often the best first build: the knowledge exists, nobody can find it.
Document review support
First-pass classification and issue spotting across disclosure or due diligence sets, to direct human attention.
Drafting against house style
First drafts from structured inputs and firm precedents, for fee earner review. Past the blank page.
Matter intake and conflicts support
Extract and structure intake information, surfacing potential issues for the conflicts team.
The gate
What assurance will ask for
We produce it during delivery. Cheaper, and more likely to be accurate.
- Processing entirely within the firm’s boundary, documented and demonstrable
- Matter-level access control enforced at query time
- A written position on privilege and confidentiality for client and insurer questions
- Retention and logging covering prompts and outputs as well as documents
- Supervision arrangements consistent with SRA expectations
- Answers ready for the AI section of client tenders and outside counsel guidelines
Illustrative scenario. A composite of how an engagement typically runs, not a specific client.
Illustrative: a commercial firm’s know-how project
Fee earners want the firm’s own prior advice and precedent clauses without asking three partners who might remember. The corpus is entirely privileged, and several clients restrict offshore processing.
That decides the architecture: self-hosted inside the firm’s network, no component reaching an external API. Including embedding, which teams often miss: they self-host inference carefully, then send the whole corpus to a hosted embedding service.
The critical decision is matter-level access control, resolved per user at query time. Without it, one client’s material eventually reaches a fee earner acting for the other side. A breached professional obligation, not a bug to fix later.
The firm gets a written processing position for clients and its insurer. It has commercial value in tenders too.
Questions from this sector
Does using AI on client files waive privilege?
That is for the firm’s own risk and compliance advice, and turns on the specifics. Firms comfortable proceeding can generally show the material never left their control. That is an architectural property, established by design.
Our clients ask about AI in tenders. What do they want to see?
Specifics: where processing happens, whether their material trains models, who can access it, what is retained and for how long, and what supervision applies to AI-assisted work. A firm with written answers beats one drafting them under deadline for every tender.
Can this work if we cannot use any external service at all?
Yes. Fully self-hosted, including the embedding model, with nothing crossing the firm’s perimeter. For firms with strict client restrictions it is the right answer.
Next step
Start with a 30-minute call
No deck. Tell us the problem. We will say whether AI is the right tool, what it would take and roughly what it would cost.