Brennholt Legal
Introduction
Twenty years of precedent, searchable in a sentence

The brief
The firm’s best work was locked in its document system
Brennholt Legal is a commercial firm of 85 lawyers. Two decades of advice, contracts and court filings sat in a document management system that could only be searched by file name and matter number. Associates rebuilt clauses that already existed, and finding a relevant precedent meant asking around. Client confidentiality ruled out any public AI tool.
Before
- Associate needs a precedent
- Searches by file name
- Asks colleagues
- Opens dozens of files
- Drafts from scratch anyway
With Zephyr
- Associate asks a question
- System retrieves permitted documents
- Answer cites exact paragraphs
- Associate checks the source
- Drafts from the firm’s own best work
What we did
A private search system that shows its sources
We indexed 180,000 documents inside the firm’s own cloud tenancy, keeping the matter-level permissions from the document system so that nobody can retrieve what they could not already open. Lawyers ask questions in German, English or Hungarian and get an answer with links to the exact paragraphs it rests on. Before rollout, six partners wrote 300 test questions and scored the answers blind. We tuned until they were satisfied, and we wrote the firm’s AI use policy in parallel.
- Document inventory and clean-up rules
- Indexing inside the firm’s own tenancy
- Matter-level permission mirroring
- 300-question partner-written test set
- Blind review and tuning
- AI use policy and associate training
The outcome
Results
92%
of answers judged correct with the right source in blind review
85
lawyers using it every week
−60%
time to find a starting precedent
The system has been in daily use since June 2025. The questions it cannot answer are reviewed monthly by the knowledge partner, which has turned out to be the firm’s most useful map of where its know-how is thin.
“Every answer comes with the paragraph it relies on. That is the only reason a lawyer will trust it.”
What was involved
- Private cloud deployment
- Permission-aware retrieval
- Paragraph citations
- Blind evaluation
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