HoneyHive

HoneyHive is a specialized observability platform designed for monitoring, debugging, and improving AI agents operating in production environments. It serves as a unified layer that brings together distributed tracing, real-time evaluation, session replay, and collaborative annotation tools, enabling engineering, product, and operations teams to maintain high-quality agent behavior across the entire lifecycle. At its core, HoneyHive provides distributed tracing powered by OpenTelemetry, which allows users to instrument any agent built on any technology stack. The system captures end-to-end traces of agent interactions, including inputs, outputs, intermediate steps, and calls to large language models (LLMs), vector databases, or external APIs. This tracing works across more than 100 LLMs and numerous agent frameworks, giving teams a single source of truth for understanding how an agent processes requests. By drilling into individual traces, engineers can identify latency bottlenecks, unexpected branching, token consumption patterns, or logic errors that lead to incorrect responses. Beyond tracing, HoneyHive offers online evaluation capabilities. Users can define custom evaluation criteria—such as response accuracy, safety constraints, or adherence to system prompts—and run live evaluations against production traffic. When an agent produces an output that fails a check, the platform immediately flags the event, alerts the relevant team, and preserves the full context for root cause analysis. This continuous feedback loop helps catch regressions before they affect end users. The platform also includes session replay functionality. Teams can replay entire chat sessions or multi-turn interactions exactly as they occurred in production, stepping through each turn, tool call,