Langwatch
The platform for LLM evaluations and AI agent testing
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What is Langwatch?
LangWatch is an open-source LLMOps platform that helps teams collaboratively debug, analyze, and iterate on their LLM applications. It provides comprehensive observability by automatically tracking every LLM call, tool usage, and user interaction with detailed traces, spans, and metadata, allowing teams to see the full conversation flow and identify bottlenecks in production.
Key features include LLM observability with real-time tracing and debugging, evaluations (both offline CI/CD and online real-time), agent simulations for testing complex agentic systems, prompt management with versioning and multi-prompt comparison, auto-prompt optimization using DSPy, dataset management that converts production traces into reusable test cases, and collaborative workflows for engineers, product managers, and domain experts to work together on AI quality.
LangWatch is designed for AI engineers, data scientists, product managers, and domain experts building LLM-powered applications. It is trusted by AI-first companies, B2B SaaS, and fintech innovators, including enterprises that need to ensure reliability, safety, and efficiency in their AI systems. The platform integrates with all major LLM providers and frameworks through OpenTelemetry-native support with Python, TypeScript, and Go SDKs.
Langwatch pricing
Pricing model: Freemium
LangWatch offers a free Developer plan with all platform features, 50,000 events per month, 14 days data access, 2 users, 3 scenarios, 3 simulations, 3 custom evaluations, and community support (GitHub & Discord). The Growth plan starts at €59/core-seat/month with all platform features, 200,000 events included plus €0.0005 per additional event, 30 days data retention (custom retention available at €3/GB), unlimited lite-users, unlimited eval scores/simulations/prompts, 20 users (volume discount above 20 users), and private Slack/Teams support. Enterprise/Regulated plan offers custom pricing with premium support, on-prem or hosted deployment, custom data retention, custom SSO/RBAC, audit logs, uptime & support SLA, ISO27001 reports, and billing via AWS/Google/Azure Marketplace. Additional usage pay-as-you-go is $0.0006 per event with volume discounts available.
Langwatch pros
- Open-source platform with over 5,600 GitHub stars
- 780,000+ monthly installs demonstrating wide adoption
- 900,000+ daily evaluations to prevent hallucinations
- OpenTelemetry-native integration with any LLM or framework
- Comprehensive observability with detailed traces and spans
- Agent simulations for testing complex multi-step agentic behavior
- DSPy-based auto-prompt optimization for systematic improvement
- Free Developer plan with 50,000 events per month
- Convert production traces into reusable test datasets
- Real-time evaluations with custom evals for product-specific quality
- Feature-flag-style prompt deployment with full traceability
- PII detection and auto-redaction for data privacy
- Jailbreaking and prompt injection safeguards built-in
- Collaborative workflows bridging engineers and non-technical stakeholders
- Self-hosted and on-prem deployment options available
- ISO27001 and SOC2 certified for enterprise compliance
- No data lock-in with export capabilities and API access
- Multi-agent graph tracing for complex agent systems
- Thread tracking for conversations, sessions, and users
- Cost and token tracking with detailed operational expense visibility
Langwatch cons
- Free tier limited to 14 days data access only
- Developer plan restricted to 2 users maximum
- Free tier only includes 3 scenarios, 3 simulations, and 3 custom evaluations
- Growth plan charges €0.0005 per event beyond 200,000 included events
- Custom data retention costs extra at €3/GB on Growth plan
- Pay-as-you-go pricing at $0.0006 per event for additional usage
- Enterprise features require talking to sales with custom pricing
- Community support on free tier limited to GitHub and Discord only
- Growth plan limited to 30 days data retention unless paying extra
- Volume discounts only available above 20 users on Growth plan
Frequently asked questions about Langwatch
How does LangWatch work?
LangWatch works by adding a few lines of SDK code to your existing application. The Python, TypeScript, or Go SDK automatically captures all LLM calls and interactions. You can then view everything happening in real-time through the dashboard, click into any trace to see exactly what went wrong, and debug issues easily. The platform is based on OpenTelemetry and integrates with all major LLM providers and frameworks without requiring code changes.
What is LLM observability?
LLM observability is the ability to see what's happening inside your LLM applications. LangWatch tracks every interaction, helps debug issues, and shows how AI systems actually work in production. Every LLM call, tool usage, and user interaction is automatically tracked with detailed traces, spans, and metadata, allowing you to see the full conversation flow, identify bottlenecks, and understand exactly how your AI applications behave.
What are LLM evaluations?
LLM evaluations are custom tests that measure quality specific to your product. LangWatch allows you to create and tune custom evals that run in real-time, including LLM-as-judge evals, code evals, and session evals. You can run batch tests and experiments directly from the platform or your code, track the impact of every change across prompts and agent pipelines, and automatically execute your full test suite for both pre-release testing and production monitoring.
Is LangWatch self-hosted available?
Yes, LangWatch is fully open-source and can be run locally or self-hosted. The Enterprise/Regulated plan offers premium support with on-prem or hosted deployment options including hybrid, self-hosted, and on-prem configurations for high volume or privacy-sensitive data. This provides alternative hosting options for organizations with specific data residency or security requirements.
How does LangWatch compare to Langfuse or LangSmith?
LangWatch is described as the #1 AI engineering platform to test AI agents pre- and in-production. It is the most open and flexible platform for LLM observability based on OpenTelemetry, integrating with all major LLM providers, frameworks, and tools. Unlike some competitors, LangWatch offers a developer-first but collaborative platform that enables non-technical team members to contribute to AI quality through an intuitive UI, and includes DSPy-based auto-prompt optimization not commonly found in other platforms.
What models and frameworks does LangWatch support and how do I integrate?
LangWatch works with any LLM or agent framework through its OpenTelemetry-native architecture. It supports Python SDK, TypeScript SDK, and Go SDK for logging traces. The platform integrates with all major LLM providers and AI agent frameworks without data lock-in. Integration is designed to be straightforward with minimal configuration - you install the SDK (pip install langwatch for Python), configure it with langwatch.setup(), and your LLM calls are automatically tracked and visible in the dashboard.
Can I try LangWatch for free?
Yes, you can sign up for free at app.langwatch.ai to get started with the Developer plan. The free tier includes all platform features, 50,000 events per month, 14 days data access, 2 users, 3 scenarios, 3 simulations, and 3 custom evaluations with community support via GitHub and Discord. You can also try the Growth plan for free to access 200,000 events included, 30 days data retention, and unlimited eval scores, simulations, and prompts.
How does LangWatch handle security and compliance?
LangWatch is ISO27001 and SOC2 certified with GDPR controlled compliance. It offers role-based access controls (RBAC) for organization, project, and team levels. Enterprise plans include custom SSO (Okta, AzureAD/EntraID), SSO enforcement, audit logs, data retention management, and data region options (EU, US, CA, APAC). The platform also includes built-in safeguards for PII detection and auto-redaction, jailbreaking and prompt injection protection, content moderation, and custom guardrails.
How can I contribute to the project?
LangWatch is an open-source platform with over 5,600 GitHub stars, indicating an active open-source community. The platform accepts traces via standard OpenTelemetry Protocol (OTLP) endpoints, making it interoperable with the broader ecosystem. Community support is available through GitHub and Discord for the free Developer tier, where users can engage with the community, report issues, and contribute to the project.
What is Agent Simulations and when should I use it?
Agent Simulations are for testing complex agentic AI by running thousands of synthetic conversations across scenarios, languages, and edge cases. They are the new unit tests for AI agents - you can simulate end-to-end agentic systems, catch regressions, and ship autonomous agents with confidence. Use Agent Simulations when you need to test multi-step agent behavior before release, validate changes to prompts or models, or simulate real-world conversations to ensure your AI agents behave correctly across different scenarios and edge cases.