Clausehound applies AI to a legal document repository, and its design addresses the specific way generic AI fails on contracts: an answer with no traceable source is useless to a lawyer.
Multi-layered AI prompting works against self-curated collections rather than an undifferentiated pile, with quality control and contextual sourcing baked into each response – so an answer points back to the clauses it came from. Document data structuring tags and models the underlying content, which is what enables comparative research: finding how a clause varies across a hundred agreements rather than reading them serially. Enhanced search runs quality-control-driven queries over the same structure.
Curated collections are the part that takes work up front – the system is only as good as how the repository is organised. That is real effort, and worth understanding before adoption rather than after. As always with legal AI, output informs professional judgement rather than replacing it.
