AI Readiness Assessment for Legal Services

Two weeks and a clear answer beats six months of pilots that never reach production. The assessment exists to kill the bad ideas early and fund the good ones properly.

In legal services, privilege and confidentiality mean data handling is scrutinised more than model performance. That single fact reshapes how ai readiness assessment has to be built here, the guardrails, the approval points and the evidence trail are design inputs rather than things bolted on before go-live.

The workload we are most often asked to take on first is matter summarisation, usually integrated against billing systems. Every engagement opens with a measurement: the cycle time, the cost per transaction, or the error rate we are being asked to move.

Built by engineers who ship production systems, not by a practice that subcontracts the build. You own the code, the models where they are open-weight, and the documentation to run it without us.