What it is
AgentOps-AI provides a Python SDK designed for monitoring AI agents, tracking costs associated with large language models (LLMs), and benchmarking performance. It integrates seamlessly with various LLMs and agent frameworks, making it a valuable resource for developers and researchers in the AI field.
Gabriel’s notes
Python SDK for agent monitoring, LLM cost tracking, benchmarking, and more. Integrates with most LLMs and agent frameworks like CrewAI, Langchain, and Autogen
Good fit if you want to:
- automate repetitive workflows and connect apps without custom code.
- generate, edit, or enhance creative assets (images, design, branding).
Pricing snapshot (auto-enriched): Free tier available with up to 5,000 events; pricing is usage-based starting at $40 per month for the Pro plan with unlimited events and log retention; custom enterprise pricing available.
Work-use / compliance snapshot (auto-enriched): AgentOps is suitable for workplace use with enterprise features including on-premises deployment, and compliance with SOC 2 and HIPAA available in the Enterprise tier, supporting secure data handling and monitoring, though specific details on training usage, retention, and SSO availability are not explicitly stated.
Alternatives (auto-enriched): Alternative: LangSmith | Comparison: LangSmith offers virtually no performance overhead, making it ideal for performance-critical production environments compared to AgentOps which has moderate overhead. Alternative: Langfuse | Comparison: Langfuse provides deep prompt-level observability but introduces slightly higher latency overhead than AgentOps.
Before you adopt it: check the README, license, recent commits, and open issues to gauge maintenance and fit.
Note: pricing and policy details can change—verify on the official site before making decisions.