A written adoption map
An audit of your legal workflows: where AI pays, where it does not, and in what order — on paper, with the costs and risks stated plainly.
Consultancy for firms, law departments, and boards adopting AI: use-cases, tools, governance, and the safeguards that keep privilege and confidentiality intact.
The firm advises organisations that want AI working inside their legal function — not as a demo, but in the daily flow of intake, drafting, review, and correspondence. Engagements typically open with an audit of the workflows worth automating, then proceed through tool selection, confidentiality and privilege safeguards, governance policies, and a supervised rollout. The firm implements AI in its own trilingual practice; the advice comes from operating it, not observing it.
The firm treats an AI rollout the way it treats a dispute: map the terrain before moving. It starts from the organisation's actual matters and documents, selects the narrowest tool that solves a real bottleneck, and puts a human-approval gate on anything that leaves the building. Policies are written to be enforced, not framed. What worked — and what failed — in the firm's own implementation is what shapes the advice.
An audit of your legal workflows: where AI pays, where it does not, and in what order — on paper, with the costs and risks stated plainly.
The advice comes from a firm that implements AI in its own trilingual practice — intake, document workflows, correspondence — under human review.
Usage policies, human-review gates, and audit trails written to be enforced — so AI-assisted work remains defensible work.
Every recommendation is screened against privilege, client confidentiality, and data-protection duties before it reaches your stack.
The consultancy is grounded in the firm's own implementation: an AI-assisted, trilingual practice platform for intake, scheduling, and document preparation — every output gated behind human approval.
Document workflows designed so AI prepares from firm-approved templates only, with citations required and partner sign-off before anything is sent.
Designing which document classes may pass through which systems, so efficiency gains never touch the most sensitive tier of client material.
A phased introduction — training, sandboxing, then live use with review checkpoints — turning an informal habit into a governed capability.
Described in abbreviated, anonymised form to preserve client confidentiality.
Yes — with the right architecture. It depends on where the data goes, what the vendor may retain, and which safeguards sit in between. The engagement's first deliverable maps exactly that for your stack, before any tool touches a client file.
The repetitive, template-shaped ones: intake summaries, first-draft correspondence, document assembly from approved precedents. High-judgment work — strategy, advocacy, advice — stays human. The adoption map ranks your workflows by gain and by risk.
You need one now, even before adopting anything — informal use is already happening in most organisations. A short, enforceable policy with human-review gates protects privilege before the first licence is bought.
It depends on your role in the system and the data involved. The assessment reads your intended uses against the applicable framework — the EU AI Act where it reaches you, and the data-protection law that governs your client material — and states what is required, in plain language.