Compare AgentOps with top alternatives in the enterprise agents category. Find detailed side-by-side comparisons to help you choose the best tool for your needs.
These tools are commonly compared with AgentOps and offer similar functionality.
AI Observability
LangChain’s platform for tracing, debugging, evaluating, monitoring, and operating LLM applications and agent workflows.
LLM observability
an open-source AI gateway and LLM observability platform for routing, debugging, analyzing, and improving AI applications.
AI observability
an AI observability, evaluation and prompt-iteration platform for shipping reliable LLM products
Analytics & Monitoring
Experiment tracking and model evaluation used in agent development.
Other tools in the enterprise agents category that you might want to compare with AgentOps.
Enterprise Agents
Adept AI licenses its ACT-1 Action Transformer technology to enterprise partners, enabling them to build AI agents that visually control any computer software using natural language commands. Through its partnership model, Adept provides screen-reading AI models, proprietary training datasets, and technical consultation for building custom agentic automation solutions—offering an alternative to traditional RPA platforms for organizations with complex, multi-application workflows.
Enterprise Agents
Enterprise content management platform with integrated AI features including AI Assistant for conversational queries, Agentic AI for automated content orchestration, and Generative AI for brand-aware copy and image creation.
Enterprise Agents
Enterprise-grade security platforms that protect, monitor, and govern AI agents across their full lifecycle — from development through production deployment — with unified observability, threat detection, and compliance controls.
Enterprise Agents
All-in-one LLM development platform. Manage prompts, run evaluations, and monitor AI apps in production. Open-source with team collaboration features.
Enterprise Agents
Airbyte is a data integration platform that syncs data from apps, APIs, databases, and files into warehouses, lakes, and AI systems. It helps teams build a context layer for AI agents by making enterprise data accessible and up to date.
Enterprise Agents
AWS's AI-powered assistant designed to help businesses with coding, analysis, and workplace productivity tasks.
💡 Pro tip: Most tools offer free trials or free tiers. Test 2-3 options side-by-side to see which fits your workflow best.
Just two lines: import the AgentOps SDK and call the init function with your API key. The SDK automatically instruments supported frameworks.
AgentOps supports a wide range of frameworks including CrewAI, AutoGen, LangChain, OpenAI Agents SDK, Cohere, Mistral, LiteLLM, and AG2. Custom agents can be instrumented via the Python or TypeScript SDK.
Yes. The entire AgentOps platform is open source under the MIT license and can be self-hosted for teams that need full data control or air-gapped deployments.
AgentOps is framework-agnostic and open source, while LangSmith is tightly integrated with the LangChain ecosystem. AgentOps emphasizes agent-level observability with time travel debugging, whereas LangSmith focuses on LLM chain tracing and evaluation.
Time travel debugging lets you replay an agent session step by step, examining every LLM call, tool invocation, and decision point in sequence to diagnose exactly where and why a workflow succeeded or failed.
Yes, the free tier includes up to 5,000 events per month with core observability features. The Pro plan starts at $40/month for higher volumes, and Enterprise pricing is available by contacting sales.
Compare features, test the interface, and see if it fits your workflow.