About HoneyHive
HoneyHive is an AI observability and evaluation platform designed to help engineering teams build, monitor, and govern production-grade AI agents and applications. By providing a unified interface that works across any model, framework, or agent runtime, the platform allows teams to move beyond simple completions to complex, multi-step agentic workflows. It bridges the gap between development and production by offering a suite of tools for distributed tracing, real-time monitoring, and systematic evaluation, ensuring that AI systems remain reliable, cost-effective, and safe as they scale.
The core of the platform revolves around its distributed tracing and evaluation capabilities. Users can instrument end-to-end applications to track every component of a request, including prompts, retrieval steps, tool calls, and model outputs. This visibility is paired with a library of over 25 pre-built evaluators that continuously analyze live traffic for quality and safety. Additionally, the experiment module allows developers to run automated test suites within CI/CD pipelines, comparing different model versions or prompt configurations to catch regressions before they reach the end user.
HoneyHive is particularly well-suited for AI engineers, product managers, and domain experts working in startups or large enterprises. It facilitates collaboration through an artifact management system that serves as a single source of truth for prompts, datasets, and metrics, which are kept in sync between the web UI and the code. This makes it ideal for teams that need to maintain high standards of reliability in sensitive industries like finance or healthcare, where SOC-2, GDPR, and HIPAA compliance are critical requirements.
What sets HoneyHive apart is its OpenTelemetry-native architecture and its flexible deployment options. Unlike closed-source observability tools, it adheres to open standards, making it easier to integrate into existing technical stacks without vendor lock-in. Furthermore, it offers diverse hosting solutions, including multi-tenant SaaS, dedicated SaaS, and self-hosted private cloud options, giving organizations full control over their data residency and security posture.
HoneyHive FAQs
What types of AI components can HoneyHive trace?
HoneyHive provides end-to-end instrumentation for prompts, retrieval steps, tool calls, Model Context Protocol (MCP) servers, and model outputs. This allows teams to visualize the entire execution flow of an agentic application to identify and fix bottlenecks or errors quickly.
Does HoneyHive support automated testing in CI/CD?
Yes, the platform includes an experiments module specifically designed to validate agents pre-deployment on large test suites. It allows you to compare different versions and catch regressions within your existing CI/CD pipelines before changes are pushed to production.
What compliance standards does the platform meet?
HoneyHive is designed for enterprise-grade security and is compliant with SOC-2, GDPR, and HIPAA standards. This makes it suitable for organizations handling sensitive data in regulated industries like healthcare and finance.
Can I host HoneyHive on my own infrastructure?
Yes, Enterprise customers have the option to choose between multi-tenant SaaS, dedicated SaaS, or a self-hosted private cloud deployment. This flexibility ensures that organizations can meet specific data residency and privacy requirements.
How many events are included in the free tier?
The Developer plan is free and includes up to 10,000 events per month. It also supports up to 5 users and a single workspace with 30 days of data retention.
