LangWatch

LangWatch is an observability and analytics platform designed for monitoring LLM applications and AI agents in production. It provides real-time visibility into agent performance, quality, costs, and user experience through comprehensive tracing, automated evaluations, and customizable dashboards. The platform helps teams ensure their agents maintain quality standards while optimizing costs and identifying issues before they impact users.

The platform captures detailed traces of every agent interaction including prompts, completions, tool calls, retrieval steps, and metadata. These traces are automatically evaluated against configurable quality checks — sentiment analysis, PII detection, topic adherence, toxicity filtering, and custom business rules. Failed checks can trigger alerts, block responses, or flag interactions for human review.

LangWatch's analytics engine provides insights into agent usage patterns, user satisfaction, conversation flows, and cost trends. Custom dashboards can track business-specific KPIs like resolution rates, escalation frequency, and user engagement. The platform identifies conversation drop-off points and common failure patterns to guide agent improvement.

Integration is straightforward with SDKs for Python and TypeScript that auto-instrument popular frameworks including LangChain, LlamaIndex, OpenAI, and Anthropic. A REST API enables integration with any language or framework. The platform supports both cloud-hosted and self-hosted deployments.

LangWatch's guardrails feature enables real-time content filtering and quality enforcement before responses reach users. This includes PII redaction, topic restriction, response length enforcement, and custom validation rules. The combination of monitoring and guardrails makes LangWatch both an observability tool and an active safety layer for production agent systems.