Check whether your AI initiative has enough traceable evidence for a credible value review, and receive a readiness score, evidence gaps, and clear next steps.
Turn your AI pilot data into a traceable decision pack with TCO, ROI, NPV, payback, sensitivity analysis, evidence gaps, risks, and clear next steps.
Three reviewer lenses audit an AI agent's or contractor's done report, cross-examine each other, and give an accept/do-not-accept recommendation.
Three AI reviewer lenses audit your grant narrative for reviewer fatigue, eligibility gaps, and weak impact proof, then cross-examine each other. No funding outcome guaranteed.
Review an AI Skill before installation or publication. Get a concrete verdict with evidence, permissions, secret risks, license constraints, and the safest next step.
This agent helps Python teams using the Anthropic or OpenAI SDK safely cut LLM spend without risking regressions. With zero code changes, it maps call sites and runs your test scenarios to rank token waste from missed prompt caching or heavy model tiers. It tests fixes in isolated git worktrees, enforcing a strict "do-no-harm" gate that reverts any patch failing to preserve behavior. It delivers a clear savings audit that converts into verified, behavior-preserving code patches upon opt-in.
Stuck on a business decision? Three AI executive lenses (Strategy, Tech, Growth) review it in turn, cross-examine each other, and give one recommendation. Not legal or financial advice.
Analysez logs, diagnostics, erreurs et éléments techniques fournis afin d’identifier des causes probables, prioriser les anomalies et préparer un plan de correction.