AI implementation for law firms and legal teams
We build AI systems for legal teams that work from your own documents, cite the passage behind every answer, and run inside your environment.
Confidentiality decides the architecture
A legal team's expertise is already written down, in briefs, precedents and advice given once and then filed. What it costs to reuse is the time of someone senior enough to know which version still holds.
Confidentiality is why these systems get built the way we build them. Everything runs on your accounts, reads under the access rules your systems already enforce, and cites the document it drew from, so a lawyer checks the answer rather than taking it on trust.
The system we built for a legal services firm
Turning case material into checkable briefs
Dense client documents become structured briefs a lawyer can check against the source, with the tone and the audience chosen per brief.
Read the case study: How a legal services firm automated case brief summaries
What running this on matter material takes
These are not added at the end. They are the reason the build takes the shape it does.
- Your permissions, checked when the question is asked
- Access is evaluated for the person asking, in your own systems. Matter material stays visible only to the people it was already visible to.
- A source under every answer
- Document, section and a link back. An answer a lawyer cannot trace to the document it came from is not an answer they can use.
- A record of what was asked and answered
- Every question, every response and every source used, kept so the system can be examined afterwards rather than trusted in advance.
- Your documents are not used to train a model
- They are retrieved for a single answer and passed as context. Processing location and retention are agreed in writing first.
Questions we get from legal teams
The system runs on your accounts and reads from where your documents already sit, under the access rules those systems enforce. Where a frontier model is called, the processing location and the retention period are agreed in writing before anything is sent. Nothing is used to train a shared model.
Every answer shows the passage it came from, so a lawyer verifies rather than trusts. Before launch the system is scored against a set of real questions with answers agreed by someone who owns the subject, and you keep that set so the same score can be rerun after any change.
It does not give legal advice and it does not answer outside the documents it was given. The out of scope questions are agreed in writing before launch, and the system declines them rather than reaching for the model's general knowledge. A system that answers everything is the failure mode.
The code, the prompts, the configuration and the evaluation set, in your repository and running on your accounts. Nothing depends on us continuing, and there is no licence to keep paying to keep the system running.
Name one document task worth automating
Tell us which document work takes the most fee earner time, and where the source material sits. We will tell you what it would take to build, and how we would prove it works.