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Tools that help teams improve AI agent quality, latency and cost using evidence from agent runs, evaluations and code.
| Company | Description | Matching products |
|---|---|---|
| LangChain | LangChain provides the engineering platform (LangSmith) and open source frameworks developers use to build, test, and deploy reliable AI agents. | |
| Arize AI, Inc. | AI observability and model evaluation platform company providing the AI engineering platform for self-improving agents. | |
| Lemma | Production monitoring for AI agents. Surfaces silent failures, pulls context across traces, and helps teams improve agents before users churn. | |
| Moda | Continual learning layer for AI agents. Analyzes production conversations to surface user intent, agent failures, and frustration causes, then feeds validated improvements back into the agent harness. | |
| Roark | Simulation testing and evals platform for voice and chat AI agents. Simulate every scenario before launch, score every production call on audio-native metrics. |
| Lucidic AI | The training and optimization platform for reliable AI agents. Lucidic AI builds the training and optimization layer for AI agents, enabling enterprises to measure, improve, and safely deploy agents through parameterization, targeted simulations, and automated optimization. |
| TraceRoot | TraceRoot is an open-source observability and self-healing platform for AI agents that captures traces, monitors production issues, and automates debugging and fix generation. |
| Caveman | Caveman builds local context compression, coding-agent tools, and TypeScript and Python middleware. It cuts AI agent token costs through output compression, input compression, model routing, and caching. |
| Papaya | Papaya analyzes AI agent traces and code to improve quality, reduce latency, and reduce cost. |