CheckOps
HoneyHive
HoneyHive is an agent observability and evaluation platform for tracing prompts and tool calls, scoring production quality, detecting drift and running offline evals and regression suites built from real cases.
- SaaS
- Free tier
- Paid
- LLM Observability
- Observability
- AI-enabled testing
- LLM Eval
- Production monitoring & observability
- Release & CI gates
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Introduction
HoneyHive covers the main jobs of agent quality in one product. You inspect every prompt, tool call, output and handoff; score agent quality and safety on live traffic; track quality, cost, latency and outcomes over time; and detect behaviour drift with the traces behind it.
Offline, you evaluate agents against datasets before production and build regression suites from real production cases. Expert review becomes reusable evaluation data, and prompts can be versioned, tested and deployed.
Features
- Tracing: Prompts, tool calls and handoffs.
- Online scoring: Quality and safety on live traffic.
- Drift detection: Spot behaviour changes.
- Offline evals: Datasets before release.
- Regression suites: Built from production cases.
- Prompt management: Version, test and deploy.
Pros
- Self-hosting option: Available on Enterprise.
- Startup discounts: For companies under $5M raised.
Cons
- Enterprise for scale: Higher limits need Enterprise.
Usage and Links (Example)
- Start free and add the SDK to your agent.
- Configure online evaluators for quality and safety.
- Promote failing production traces into a regression suite.
Resources:
Pricing
HoneyHive lets you start building for free; Enterprise adds higher limits, dedicated support and self-hosting on major clouds. Startups with under $5M raised can ask for discounts.
Recommended for?
- Teams moving agents from pilot to production.
Conclusion
HoneyHive is a well-rounded agent observability and eval platform.
Its self-hosting on Enterprise suits data-sensitive teams.
On CheckOps, HoneyHive is filed under the Production monitoring & observability and Release & CI gates stages. Related tools listed here include Langfuse, LangSmith, Braintrust, Arize Phoenix, Galileo and W&B Weave. Before standardising on one, compare recent maintenance activity, the pricing model as your usage grows, and the integrations you rely on today. Information on this page was verified against the official website, documentation and repository on 11 November 2026.
Alternatives
Other tools on CheckOps that cover similar ground. Open a page, or compare one with HoneyHive side by side.
LLangfuseLangfuse is an open-source platform for LLM traces, prompts, and evals. Self-hosting is free; Langfuse Cloud is paid after a hobby tier.Compare with HoneyHive
LLangSmithLangSmith is LangChain's platform for observability and evaluation of LLM applications and agents, including offline and online evals.Compare with HoneyHive
BBraintrustBraintrust is a hosted platform for AI evals and agent observability: trace production, turn patterns into evals, score releases, and query it from your IDE via MCP.Compare with HoneyHive
AArize PhoenixArize Phoenix is an open-source (Elastic License 2.0) AI observability and evaluation tool for tracing, evaluating and improving LLM apps and agents, with a hosted Arize AX tier.Compare with HoneyHive
GGalileoGalileo is an AI observability and eval engineering platform that builds datasets, tunes evaluation metrics and turns offline evals into production guardrails for AI apps and agents.Compare with HoneyHive
WW&B WeaveW&B Weave is an Apache-2.0 toolkit from Weights & Biases for tracing and evaluating AI agents and LLM apps, with scorers, datasets, evaluations and an online UI.Compare with HoneyHive