Selected experience
What does this look like in practice?
Our work has repeatedly involved listening carefully to clients, understanding the real problem and balancing out-of-the-box technology with collaboration and customisation.
Case study 1 — French insurance group
AI-assisted contract risk review
A major French insurance group was rolling out a digital commercial platform serving architects, engineers and design firms. We helped design and refine AI-assisted search tools to locate sensitive provisions that mattered to those professionals.
The work involved translating contract concepts into structured, machine-usable review criteria and refining the tools around the client's real-world needs.
Good legal AI starts with understanding what the client needs to know — not simply what the technology can detect.
Case study 2 — Transportation & supply-chain legal services provider
Building for a new industry
Over several years, we worked with an alternative legal services provider developing AI-enabled search tools to locate contract risk in the shipping and warehousing sector. Together, we developed and released almost 100 specialised search algorithms, monitored their real-world use and made rapid rule-based and model-based improvements.
The solution was ultimately deployed to approximately 1,000 end users.
When the technology, industry and training data are new, close collaboration and rapid iteration can matter more than getting the first version perfect.
Case study 3 — U.S. professional services firm
Making legacy data useful
A professional services firm had roughly 15,000 legacy documents in a CLM system whose data it did not fully trust. Rather than re-extracting every possible field, we helped identify which existing data was reliable enough to retain and which critical fields should be extracted again from the source documents.
We extracted 25 key data points across the legacy dataset and recommended and configured existing fields for ongoing M&A due-diligence reviews.
The right answer is not always ‘extract everything.' Focus effort where it creates the most value.