PromptLayer
Prompt management, versioning, and observability workspace for non-technical teams
Observability and evaluation platform for AI agents and LLM applications
HoneyHive is an AI observability and evaluation platform offering tracing, evals, testing, and production monitoring for LLM apps and agents, with data-residency support and a sales-led pricing model.
HoneyHive helps engineering, product, and subject-matter teams collaborate on building reliable AI applications. It combines distributed tracing of LLM and agent calls, offline and online evaluation, dataset management, and prompt experimentation with production monitoring — so teams can debug failures, measure quality, and catch regressions across the development lifecycle. A distinguishing focus is enterprise readiness, including data-residency options, positioning HoneyHive for regulated organizations that need control over where their evaluation and trace data lives. It supports human-in-the-loop review alongside automated evaluators, letting domain experts and engineers jointly assess agent behavior. HoneyHive uses a sales-led pricing model: there is a free tier for getting started and trials, but production monitoring and enterprise features generally require an Enterprise conversation with custom pricing. As of 2026, teams should contact HoneyHive for current pricing based on usage and requirements.
HoneyHive is an enterprise-focused AI observability and evaluation platform for LLM apps and agents, combining tracing, evals, and monitoring with data-residency support and sales-led pricing.
HoneyHive is an LLMOps company building observability and evaluation tooling for teams shipping AI agents to production. It positions itself around trust and enterprise readiness.
The company serves organizations that need to observe, evaluate, and rely on mission-critical agents, offering data-residency and collaboration features under a sales-led commercial model.
HoneyHive unifies distributed tracing, offline and online evaluation, dataset management, and production monitoring, letting teams debug, measure quality, and catch regressions across the lifecycle.
It supports both automated evaluators and human-in-the-loop review, integrates via SDKs and OpenTelemetry, and emphasizes data-residency for regulated enterprises.
HoneyHive targets enterprises and cross-functional AI teams building production LLM applications and agents that require rigorous evaluation, monitoring, and data control.
AI engineers, product managers, and subject-matter experts evaluating and monitoring agents.
Engineering and AI leaders adopting LLMOps and observability tooling.
ML and platform practitioners focused on evaluation and reliability.
Enterprises running production agents that need evaluation rigor, monitoring, and data-residency control.
HoneyHive is a venture-backed startup; specific funding details are not prominently public. Verify with the vendor or funding databases.
It provides observability and evaluation for LLM applications and agents, including tracing, automated and human evaluation, testing, and production monitoring in one platform.
HoneyHive uses sales-led pricing. There is a free tier for trials, but production and enterprise use require a custom quote from their team.
Yes. HoneyHive emphasizes enterprise readiness including data-residency options, appealing to regulated organizations.
Yes. It supports evaluating agent behavior with automated evaluators and human-in-the-loop review, plus tracing of tool calls and reasoning steps.
You can use the HoneyHive SDK or OpenTelemetry-based instrumentation to capture traces of prompts, tool calls, and outputs.
Side-by-side pages for pricing, features, and best-fit use cases.
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