Eight capabilities where credentialed judgment moves model quality.
Every engagement is staffed from one or more of the practices below. Each practice is led by specialists matched to the credential and depth the task requires.
Your reward signal is only as good as the ranker. Our judges are domain specialists — clinical reviewers, licensed attorneys, senior engineers, and trained safety evaluators — ranking preferences inside their own domain of practice. A reward model that actually reflects expert judgment.
A physician-authored clinical CoT teaches the model physician-style reasoning. A mathematician-authored proof teaches proof-style reasoning. Not crowd-sourced step-by-step — expert-authored.
Jailbreak discovery, bias detection, harmful-output surfacing, and policy-compliance review — delivered by specialists who work inside your trust & safety workflows. Every finding includes reproduction steps and a recommended mitigation.
Every claim traced to a source document. Every citation verified. Every hallucination logged with reproduction steps. Built for products where a wrong answer is a liability, not a nuisance.
Model risk review, bias audits, and compliance documentation that survives enterprise procurement and regulatory inquiry. Built for AI products entering regulated markets — financial services, healthcare, government.
Entity models, taxonomies, and relationship schemas designed by ontologists. For vertical AI, enterprise search, and RAG systems where context and relationship matter more than surface text.
Planning trajectories, tool-call correctness, sub-task decomposition, workflow completion — evaluated step-by-step, not just on final output. For AI agents that act on the world.
Coherence across 100K+ token contexts. Memory recall in multi-turn sessions. Context-drift in long-running agents. The capability benchmarks don't yet capture — but your users notice.