§ Capability 02

Legal & document intelligence

Lawyer-grade analysis, with citations that actually hold up.

In legal work the dangerous failure is not the obvious mistake — it is the confident, fluent, well-cited answer that happens to be wrong. We build retrieval-augmented systems for case analysis, precedent retrieval, and contract analytics that are engineered and evaluated specifically to catch that failure mode, not to score well on a demo.

That means treating retrieval quality, faithfulness to source, and citation accuracy as separate measured axes; building adversarial evaluation sets with lawyers rather than engineers; and treating privilege and data-governance boundaries as architectural constraints from the first line of code. An analysis tool that is accurate but leaks privileged material across a wall is not a partial product — it is an unusable one.

NLPRAGRetrievalEvaluationLegal complianceDocument parsing

RAG-based case analysis

Precedent retrieval and case analysis grounded in a verified corpus, with citation checks that confirm each authority exists, was retrieved, and actually supports the claim.

Contract analytics

Clause extraction, risk flagging, and comparison across document sets with measurable efficiency gains over manual review.

Rigorous evaluation harnesses

Separate metrics for retrieval recall, groundedness, citation accuracy, and refusal calibration — plus LLM-as-judge calibrated against human lawyer review.

Privilege & compliance by design

Matter-level access boundaries, privileged content kept out of shared context, and PIPEDA / GDPR governance treated as a precondition, not a feature.

§ In practice