LangSmith

LangSmith Deployment is a purpose-built infrastructure and management layer for deploying and scaling long-running, stateful agents -- offering: - 1-click deployment to go live in minutes, - 30 API endpoints for designing custom user experiences that fit any interaction pattern - Horizontal scaling to handle bursty, long-running traffic - A persistence layer to support memory, conversational history, and async collaboration with human-in-the-loop or multi-agent workflows - Native LangSmith Studio, the agent IDE, for easy debugging, visibility, and iteration. LangSmith Observability and Evaluation is a unified observability & evals platform where teams can debug, test, and monitor AI app performance - whether building with LangChain or not. LangSmith provides an enterprise-grade observability and deployment platform for AI and agentic workloads. It enables engineering and data science teams to deploy, monitor, and optimize LLM-based applications securely on Azure Kubernetes Service. Designed for AI engineers, ML platform teams, and data scientists across industries such as financial services, healthcare, retail, and manufacturing. - Find failures fast with agent observability. Quickly debug and understand non-deterministic LLM app behavior with tracing. See what your agent is doing step by step, then fix issues to improve latency and response quality. - Evaluate your agent's performance. Evaluate your app by saving production traces to datasets, then score performance with LLM-as-Judge evaluators. Gather human feedback from subject-matter experts to assess response relevance, correctness, harmfulness, and other criteria. - Experiment with models and prompts in the Playground, and compare outputs across different prompt versions. Any teammate can use the Prompt Canvas UI to directly recommend and improve prompts. - Track business-critical metrics like costs, latency, and response quality with live dashboards, then get alerted when problems arise and drill into root cause. - Integrate seamlessly with Azure OpenAI, Cognitive Search, and Application Insights. - Scale stateful agents securely within enterprise-grade AKS environments - Reduce AI app debugging time through unified observability and tracing.