AgentOps
Developer platform for observability, monitoring, and evaluation of AI agents and LLM apps.
Updated April 2026
Overview
- Website
- agentops.ai
- Segment
- LLM Observability & Tracing
Product overview
AgentOps provides an open-source Python SDK with native integrations for frameworks like CrewAI, AutoGen, LangChain, and 400+ LLMs, enabling session replays, cost tracking, debugging, and benchmarking to take agents from prototype to production , ]. Thousands of engineers use it for reliable agent building, with customers including Microsoft, IBM, and Samsung , ]. It stands out with time-travel debugging, compliance tools like prompt injection detection, and comprehensive metrics in an intuitive dashboard ].
Revenue model
Freemium: Free Basic tier (up to 5k events/mo), Pro from $40/mo pay-as-you-go, custom Enterprise with SLA/SSO/SOC2 , ].
Moat
AgentOps's key competitive moat is its proprietary agent observability platform with a single SDK that provides native integrations across 400+ LLMs and top agent frameworks like OpenAI, CrewAI, and Autogen, enabling seamless tracking, cost monitoring, replay analytics, and troubleshooting that creates high switching costs for developers reliant on its specialized data from thousands of production agents. This is bolstered by continuous infrastructure improvements like semantic search with Pinecone, evaluation components for real-time feedback loops, and fine-tuning capabilities up to 25x cheaper using saved completions, building proprietary data and technology barriers in the nascent AgentOps market.
Headwinds
Narrow focus on agent observability may limit market size and faces competition from broader APM vendors.