HoneyHive
Evaluation and observability platform for AI agents
HoneyHive is profiled here as a Observability tool for engineering teams. Read about features, pricing, and how it compares to related options in the tools directory.
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
- Sentry
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- SigNoz
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- Datadog
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- Arize AX
Enterprise platform for AI observability and evaluation
- OpenTelemetry
Vendor-neutral standard for traces, metrics, and logs
- Prometheus
Open-source metrics monitoring and time-series database