🪢 Open source LLM engineering platform: LLM Observability, metrics, evals, prompt management, playground, datasets. Integrates with OpenTelemetry, Langchain, OpenAI SDK, LiteLLM, and more. 🍊YC W23
Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.
Next-generation AI Agent Optimization Platform: Cozeloop addresses challenges in AI agent development by providing full-lifecycle management capabilities from development, debugging, and evaluation to monitoring.
🧊 Open source LLM observability platform. One line of code to monitor, evaluate, and experiment. YC W23 🍓
Open Source TypeScript AI Agent Framework with built-in LLM Observability
The open-source LLMOps platform: prompt playground, prompt management, LLM evaluation, and LLM observability all in one place.
Laminar - open-source all-in-one platform for engineering AI products. Create data flywheel for your AI app. Traces, Evals, Datasets, Labels. YC S24.
The open source post-building layer for agents. Our environment data and evals power agent post-training (RL, SFT) and monitoring.
Build, Improve Performance, and Productionize your LLM Application with an Integrated Framework
React components for visualizing traces from AI agents
Modular, open source LLMOps stack that separates concerns: LiteLLM unifies LLM APIs, manages routing and cost controls, and ensures high-availability, while Langfuse focuses on detailed observability, prompt versioning, and performance evaluations.
A powerful AI observability framework that provides comprehensive insights into agent interactions across platforms, enabling developers to monitor, analyze, and optimize AI-driven applications with minimal integration effort.
A comprehensive solution for monitoring your AI models in production
Open-source observability for your LLM application.
🪢 Auto-generated Java Client for Langfuse API
The reliability layer between your code and LLM providers.
A Python package for tracking and analyzing LLM usage across different models and applications. It is primarily designed as a library for integration into development process of LLM-based agentic workflow tooling, providing robust tracking capabilities.
AI Observability Platform – Advanced monitoring and analytics for LLM applications with intelligent gateway. 40+ AI-specific metrics, real-time insights, OpenAI-compatible.
The reliability layer between your code and LLM providers. Hapax is a production-ready AI infrastructure layer that ensures uninterrupted AI operations through intelligent provider management and automatic failover. It is designed to address common challenges in managing AI infrastructure
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