HoneyHive vs MLflow Prompt Registry

HoneyHive is an agent observability platform for observing, evaluating, and improving AI agents in production. It captures traces that expose tool calls, prompts, and agent decisions step by step. Teams can run automated code-based checks, LLM-judge evaluations, and human reviews through annotation queues and custom rubrics. Live traffic monitoring supports score thresholds, drift detection, and email or webhook alerts, while experiments compare agent versions on datasets and track regressions before release. Integrations include LangChain, LangGraph, CrewAI, OpenAI Agents SDK, and Microsoft Copilot Studio. Tracing follows OpenTelemetry semantic conventions, allowing OTel-instrumented libraries to send data without a dedicated guide. HoneyHive also provides cost and token-cost tracking, prompt management, and tracing for LLMs, agents, and retrieval. The free Developer plan costs nothing and includes five users, one workspace, unlimited projects, 10,000 events monthly, 30-day retention, and 1,000 requests per minute. Enterprise has custom pricing and hosting options.

MLflow Prompt Registry has no write-up on Specifiction yet; its figures are above.