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    5. HoneyHive
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    Added 6/29/2026

    HoneyHive

    Evaluation and observability platform for AI agents

    HoneyHive is profiled here as a Testing tool for engineering teams. Read about features, pricing, and how it compares to related options in the tools directory.

    TestingLLMObservabilityEvaluationAgentic CapabilitiesFree
    Visit WebsiteGitHub

    Description

     HoneyHive is an evaluation and observability platform for LLM applications, founded by Dhruv Singh and Mohak Sharma through Y Combinator in 2023. Built on OpenTelemetry, it traces every step of an agent, runs evaluators on live and offline data, and turns production failures into test suites so quality improves on a continuous loop. Teams define code or model-based metrics, bring domain experts in to grade edge cases, and gate releases in CI, which connects evaluation to every stage of building an agent.

    Key Capabilities:

    • OpenTelemetry-native tracing of prompts, retrieval, and tool calls

    • Online and offline evaluators with prebuilt and custom metrics

    • Datasets curated from production failures for regression testing

    • Human review workflows for domain experts to grade outputs

    • CI integration that catches regressions before a release

    • Self-hosting in a private cloud for regulated industries

    Alternative tools

    • Gentrace

      Testing and evaluation for generative AI applications

    • Sentry

      Error tracking and performance monitoring for developers

    • QA Wolf

      Managed end-to-end test creation and maintenance service

    • Checkly

      Monitoring-as-code with Playwright-based end-to-end checks

    • Elementary

      dbt-native data observability and anomaly detection

    • Soda

      Data quality testing defined in a readable check language

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