LangWatch
verifiedPaidLLM observability and evaluation for monitoring and optimizing apps; solid dev adoption.
What it does
LangWatch is an LLM observability and evaluation platform designed to help AI teams monitor, evaluate, and optimize their LLM-powered applications. It provides full visibility into prompts, variables, tool calls, and agents across major AI frameworks, enabling faster debugging and smarter insights. LangWatch supports both offline and online checks with LLM-as-a-Judge and code-based tests, allowing users to scale evaluations in production and maintain performance. It also offers real-time monitoring with automated anomaly detection, smart alerting, and root cause analysis, along with features for annotations, labeling, and experimentations.
How to use: LangWatch integrates into any tech stack and supports various LLMs and frameworks. Users can monitor, evaluate, and get business metrics from their LLM applications, create data to iterate, and measure real ROI. Domain experts can be brought onboard to bring human evals into workflows.
Core features
- ✦LLM Observability
- ✦LLM Evaluation
- ✦LLM Optimization
- ✦AI agent testing
- ✦LLM Guardrails
- ✦LLM User Analytics
Use cases
- →Identify, debug, and resolve blindspots in AI stacks.
- →Integrate automated LLM evaluations directly into workflows.
- →Keep AI reliable and under control with real-time monitoring.
- →Improve data with human-in-the-loop workflows for annotations and labeling.
- →Automatically find the best prompt and few shot examples for the LLMs.
Pricing
Reviews
Big-picture takes: what it's for and whether it delivers. High-engagement videos from YouTube — not sponsored.
LangWatch Scenarios - AI Agent Testing
LangWatch · 14K views
Tutorials
Step-by-step: exactly how to get things done with it.
LangWatch Launches: Skills, a new and faster way to build reliable Agents
LangWatch · 136K views