What AgentOps does
AgentOps (agentops.ai) is a developer platform for building, testing, debugging, and deploying AI agents and LLM apps. The core product is an observability and “time-travel” session replay layer that captures runtime events (LLM calls, tool calls, multi-agent interactions), allowing engineers to visualize what happened, rewind and replay agent runs, and maintain an audit trail across the prototype-to-production lifecycle. The platform integrates with common agent frameworks and LLM providers via an SDK (including a Python SDK and documented REST API) and offers features such as session replays, token counts and cost tracking, replay analytics, and debugging/auditing flows (including protections the company describes around prompt-injection attacks). It is offered as a hosted service with options described on the website for self-hosting/on-prem deployments and enterprise controls like custom SSO, role-based permissions, and custom data retention. AgentOps primarily targets AI engineers and product teams that are moving agentic workflows into production and need reliability, compliance-grade logging/auditability, and faster root-cause analysis for non-deterministic or multi-step agent failures. Commercially, it follows a freemium model with a free tier and paid Pro and Enterprise plans shown on the marketing site.