Teehoo AI builds methodology, capability systems, and open collaboration samples across evaluation design, RL environments, and expert verification — purpose-built for the post-training era.
Capability scope — not operational traction figures (users, tasks, customers).
Three lines of work — evaluation, RL environments, expert verification — defining the boundary where models are not yet reliable.
Rubric systems for complex reasoning, multi-step tasks, and agent behavior. Expert-level scoring standards anchored by multi-judge agreement, with failure modes flowing back into rubric iteration — evaluation quality compounds over time.
Reproducible task environments with auditable rewards. Trajectory replay, ground-truth labeling, and reward shaping — supporting agent evaluation, tool-use verification, and multi-turn alignment.
Tier-gated global expert network providing reasoning correctness, agent trajectory review, and safety verification. Humans define what models ought to produce, not just what they currently produce.
Methodology, dimensions, and aligned public benchmarks. Progress bars below indicate capability coverage scope — not model scores.
Complex multilingual reasoning evaluation across multi-step logic, long-context, and cross-disciplinary tasks. Anchored by expert rubrics and multi-judge agreement, with continuous judge-human alignment calibration.
Agent behavior and trajectory evaluation across multi-step tool-use trajectories, error-step localization, and regression verification. Root-cause attribution replaces aggregate scoring to pinpoint real failure modes.
Model safety and red-team evaluation across adversarial prompting, jailbreak attempts, and harmful output detection. Tiered classification by harm category with risks feeding back into safeguard iteration.
Teehoo AI does not publish proprietary benchmarks. Instead, we align with public academic and industry benchmarks and extend bilingual coverage on top. "Alignment" denotes methodology-level coverage capability — not third-party certification or endorsement.
Benchmark names follow each project's official designation. "Aligned / Extending / Planned" denotes Teehoo AI's methodology-level coverage relative to each, not certification or exclusive licensing.
Methodology drafts, Distributed Expert workflow papers, compliance frameworks, and frontier observations. Drafts in progress — released as ready.
Expert-level rubric design, multi-judge agreement, and continuous judge-human alignment calibration.
Tier-gated admission, remote collaboration, and rubric × cohort matching at scale.
Dual-jurisdiction data sovereignty, in-region processing, and audit-ready trails.
From model regression to failure-loop closure — pipeline design references.
Methodology briefs, benchmark alignment progress, compliance framework updates — subscribers get them first.
Form is a frontend placeholder; production launch wires it to a compliant email service with unsubscribe controls. Research inquiries: press@teehooai.com · partnerships: partnerships@teehooai.com
