A productized evaluation and remediation service for enterprises deploying AI agents into operational workflows.
Added Aug 6, 2026
High opportunity (87%)
Enterprise teams are connecting AI agents to APIs?, databases, and internal tools, but often lack realistic evaluation sets and repeatable release criteria. This leaves them exposed to hallucinations, unsafe tool calls, security failures, poor retrieval, and outputs that do not meet business requirements.
Deliver a fixed-scope audit that maps one agent workflow, builds representative test scenarios, measures accuracy, groundedness, safety, tool-use reliability, and business outcomes, and documents failure modes. The engagement ends with remediation recommendations, an auditable scorecard, and a reusable regression test suite that the buyer can run before future releases.
Recent hiring across consulting, technology, financial services, and semiconductor environments shows enterprises moving from AI experiments to agents that execute real tasks. Connecting those agents to operational systems creates an immediate need for independent validation and governance.
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Develop evaluation infrastructure that measures model reliability for enterprise and public sector customers Ship agentic AI applications and the tooling that makes them observable, testable, and safe to deploy
Programmatic Verification: Develop rigorous, policy-aware judges and evaluations that measure genuine capability and safety beyond simple benchmarks. Close the Loop: Design and execute high-quality post-training runs (CPT, SFT, RL) to deliver frontier performance on open-source models using curated, high-signal data.
- Create advanced evaluation methods combining deterministic verification, task-specific grading, process supervision, model-based evaluation, statistical analysis, and targeted expert review. - Lead controlled experiments and comparative studies across models, prompts, tools, data strategies, and agent architectures.
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