AgentOps
Leading AI Agent Observability Company
🛡️ AgentReady threat assessment
MAESTRO 7-layer threat model + OWASP AIVSS risk score for AgentOps, derived from its capabilities.
AIVSS 6.2 · Medium
View MAESTRO 7-layer threat model →These scores are auto-generated from public information (the agent's own listing, docs, and repository) using the canonical OWASP AIVSS formula and the MAESTRO framework — an estimate for guidance, not a penetration test, audit, or certification. See the scoring methodology — every score is re-derived by the same automated method as an agent's public evidence changes.
Overview
Python SDK for AI agent monitoring, LLM cost tracking, benchmarking, and more. Integrates with most LLMs and agent frameworks including CrewAI, Langchain, Autogen, AG2, and CamelAI
Key features and capabilities
- Visualize: Visually track events such as LLM calls, tools, and multi-agent interactions.
- Time Travel Debugging: Rewind and replay agent runs with point in time precision.
- Debug and Audit: Keep a full data trail of logs, errors, and prompt injection attacks from prototype to production.
- Token Counts: Track, save, and monitor every token your agent sees.
- Cost Tracking: Manage and vizualize agent spend with up-to-date price monitoring.
- Fine-tuning: Fine-tune specialized LLMs up to 25x cheaper on saved completions.
Use cases
- From open source AI agent developer tools like AgentOps to Fortune 500 enterprises, we help clients create safe, reliable, and scalable AI agents.