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Langtrace is an open-source observability platform designed for AI applications, specifically those built with large language models (LLMs). Developed by Scale3 Labs, it addresses the challenge of monitoring, debugging, and optimizing LLM-powered systems in production. The tool provides end-to-end tracing of LLM calls, enabling developers to track latency, token usage, and errors across different models and providers. It supports popular frameworks like LangChain, LlamaIndex, and OpenAI SDK, making it easy to integrate into existing workflows. Langtrace offers both a hosted cloud version and a self-hosted option, catering to teams with varying security and compliance needs. Its core capabilities include real-time monitoring, cost analysis, and performance insights, helping teams improve response quality and reduce operational overhead. The platform is ideal for AI engineers, ML ops teams, and product developers who need visibility into their LLM applications. By simplifying observability, Langtrace empowers users to build more reliable and efficient AI systems.
4.5/5
High, consistent, and on-brand
Clean and minimal
To provide observability and monitoring for LLM-powered applications.
Integrates with LangChain, LlamaIndex, OpenAI SDK, and supports self-hosted or cloud deployment.
Freemium with paid tiers
Features with the highest value for users are highlighted here.
End-to-end LLM tracing
Token usage and latency monitoring
LangChain and OpenAI integration
Custom evaluation metrics
Self-hosted deployment option
Visual workflow debugging
Error and bottleneck identification
Integration with existing monitoring tools
AI Engineers
ML Ops Teams
Product Managers
Startups
Enterprise Teams
LangChain Developers
Research Labs
Customer Support Teams
DevOps Engineers
Freelance Developers
Free
Pro
Weekly intelligence on AI strategy, operations, and market shifts. No noise. No narrative. Direct to your inbox.
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