About
Built on research, not hype
TriageCounsel was built for legal teams who review the same agreement types repeatedly. Turn what legal has already decided into governed review outcomes — clear the repeatable, surface the exceptions, and keep judgment with lawyers when policy cannot resolve the question.
Our Approach
Most AI contract tools treat review as a single prompt and review clauses in isolation. Results vary, lack audit trails, and ignore how provisions interact.
TriageCounsel evaluates incoming agreements against your approved positions, then applies connected review across clause types. Deterministic policy engines decide; AI assists with discovery and explanation — never with authoritative outcomes.
Peer-Reviewed
TriageCounsel's architecture is backed by two accepted peer-reviewed papers: ICCS 2026 (Springer LNCS) on deterministic execution boundaries, and IEEE TPS 2026 on trust-boundary architectures with threat modeling, injection containment, and runtime enforcement.
The research shows that authoritative decisions belong in versioned deterministic logic — with AI limited to non-authoritative explanation — so outcomes stay reproducible, traceable, and defensible.
Read the research →Our Mission
Make connected contract review deterministic, auditable, and governed by approved positions — so legal teams spend less time on repeatable work and more time on judgment calls that matter.
Founder
Founded by Santhosh Guntupalli, a data engineer and AI researcher whose peer-reviewed work spans deterministic execution frameworks for hybrid AI systems (ICCS 2026, Springer LNCS) and trust-boundary architectures for auditable LLM-assisted contract risk analysis (IEEE TPS 2026).