AI Agent Reputation & Evaluation vs loopgrid
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LoopGrid is control plane for AI decision reliability. It provides a system of record for AI decisions - capture every decision immutably, replay failures with controlled overrides, and build ground truth from human corrections. Unlike traditional observability tools that only show what happened, LoopGrid lets you re-run any AI decision with a different prompt and see what would have happened. Perfect for debugging LLM agents, AI support bots, and any production AI system. | ReputAgent provides A2A evaluation infrastructure. When agents work together, reputation emerges from real work—not benchmarks. We help you build that trust infrastructure. |
Immutable Decision Ledger, Replay Engine, Human Correction Loop, Python SDK, JavaScript SDK, REST API, Self-Hosted, Apache 2.0 License | Continuous AI agent evaluation, Reputation scoring from accumulated evidence, Evaluation dimensions framework (accuracy, safety, reliability), Failure modes library with mitigations, Evaluation patterns library (LLM-as-judge, human-in-the-loop, red teaming, orchestration), Agent Playground for pre-production scrimmage testing, Ecosystem tools tracker and comparisons, Research index of agent evaluation papers, Open dataset export (CC-BY-4.0), RepKit SDK (pre-release) for logging evaluations and querying reputation, Pre-production agent testing, Agent reliability QA before launch, Ongoing evaluation in production, Safety and red teaming workflows, Routing and delegation based on trust signals, Access control and governance decisions, Comparing agent frameworks and tools, Research and benchmarking of evaluation methods, Shared vocabulary and taxonomy for agent teams |
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