LangWatch
What is LangWatch?
LangWatch is an AI observability and evaluation platform for AI product teams that turns production traces into tests, simulations, and monitoring signals before release. It combines Traces, Evaluations, Agent Simulations, and Prompt Management, with Slack and HubSpot integrations plus Python, JS/TS, and OpenTelemetry support. Customers cited on the site include Booking.com and Roojoom. Plans run Developer Free, Growth $34/month, and Enterprise / Regulated custom.
Last verifiedHow we evaluate
At a glance
- LangWatch is best for AI product teams who need to test, monitor, and optimize agents before release.
- Developer Free; Growth $34; Enterprise / Regulated Custom
- Yes — The page advertises SDKs and integrations for Python and JS/TS, plus OpenTelemetry and framework-specific agent integrations.
What does LangWatch do?
LangWatch turns production traces into evaluations, simulations, and monitoring signals so teams can test changes before they ship. It combines Prompt & Model Management, Real-time Evaluations, and Agent Simulations to compare prompts, validate multi-step behavior, and surface regressions with visual feedback. The workflow is built for both code and no-code use, so product, QA, and engineering can collaborate on the same quality checks. At scale, the platform is used by 1000's of AI developers, supports 780k+ monthly installs, and runs 900k+ daily evaluations to prevent hallucinations. Its observability layer tracks 800+ models and providers, with prompt/output tracing, latency and error alerting, and token/cost tracking. Customers cited on the site include Booking.com and Roojoom, and LangWatch also offers self-hosting for teams that need more control over deployment and data handling.
Why use LangWatch?
- It connects testing, observability, and prompt optimization in one workflow, so teams can move from trace to fix without switching tools.
- Its agent simulations are built for multi-turn and adversarial testing, which helps expose failures manual QA often misses.
- OpenTelemetry-native tracing reduces lock-in and makes it easier to plug into existing AI stacks and monitoring setups.
- Self-hosted and hybrid deployment options give teams more control over where data and workloads live.
- The platform supports both developers and non-technical users, so quality checks can be shared across engineering, product, and field experts.
Who is LangWatch for?
- AI engineers who need to catch regressions in prompts, models, and agent flows before production.
- Product managers who want shared evaluation workflows and clear feedback on AI behavior.
- QA and field experts who need no-code ways to define scenarios and review results.
- Platform teams who need observability, alerting, and deployment control across AI systems.
- Security-conscious teams who need self-hosted or hybrid deployment options.
What are LangWatch's key features?
Traces
Capture prompt and output traces with metadata-rich logs, token and cost tracking, and OpenTelemetry support for faster debugging and auditability.
Evaluations
Run real-time and offline evaluations, including structured outputs and tool calls, to catch failures before they reach users.
Agent Simulations
Simulate thousands of multi-turn conversations, including adversarial attacks, to stress-test agents and validate realistic scenarios.
Prompt Management
Version prompts, track changes, and A/B test prompt variants with visual performance feedback to improve outputs without guesswork.
Collaboration
Share evaluations, prompts, and datasets across teams with Slack and HubSpot integrations, helping engineers and PMs work from one place.
Auto-prompt optimization
Use DSPy-based optimization to tune prompts automatically, with support for batch tests and experiments across 800+ models and providers.
Role-based access controls
Control access with custom SSO/RBAC, audit logs, and self-hosted or air-gapped deployment options for privacy-sensitive teams.
Framework agnostic
Connect through Python, JS/TS, OpenTelemetry, and framework integrations like LangChain, LangGraph, and Pydantic AI without rewriting your stack.
What does LangWatch integrate with?
- OpenTelemetry
- OpenAI agents
- LiteLLM
- DSPy
- LangGraph
- LangChain
- Pydantic AI
- AWS BedRock
- Agno
- Crew AI
- Python
- JS/TS
- OpenAI
- Slack
- HubSpot
What are LangWatch's use cases?
AI engineers catch regressions
AI engineers use LangWatch to catch regressions in prompts, models, and agent flows before release, using Traces to inspect failures and Evaluations to compare runs. They can pair that with Agent Simulations to stress-test changes against realistic conversations and stop broken behavior from reaching production.
PMs review AI behavior together
Product managers use LangWatch to review AI behavior with engineering and QA, using Collaboration to share feedback and Data review & labeling to turn edge cases into reusable evaluation sets. Prompt Management helps them track changes and align on which prompt version should ship.
QA teams define no-code scenarios
QA and field experts use LangWatch to define scenarios without code, using Agent Simulations to model multi-turn conversations and Scripted simulations to cover known failure paths. They then use Evaluations to score outputs and confirm the system handles real-world cases consistently.
Platform teams monitor AI systems
Platform teams use LangWatch to monitor AI systems in production, using LLM Observability and Latency, Errors & Alerting to spot issues quickly. Framework agnostic support and Role-based access controls help them roll out oversight across different stacks while keeping deployment control tight.
How does LangWatch work?
- Connect your first app through Python, JS/TS, or OpenTelemetry, then start capturing Traces and Prompt & Output Tracing from live requests.
- Run Evaluations and Real-time Evaluations on those traces to score outputs, compare prompt versions, and surface regressions early.
- Build Agent Simulations or Scripted simulations to test multi-turn scenarios, structured outputs, and tool calls before deployment.
- Use Collaboration, Data review & labeling, and Dataset management to turn reviewer feedback into shared test sets and repeatable checks.
- Harden releases with CI/CD Evaluation Pipelines, then monitor Monitoring and Dashboards plus Trigger Alerts for ongoing production control.
How much does LangWatch cost?
Developer
Free- Get started with AI Agent
- Monitoring, evaluation
- Agent simulations
- All platform features
- 50,000 events p/m
- 14 days data access
- 2 users
- 3 Scenario's, 3 Simulations & 3 custom evaluations
- Community Support
- (Github & Discord)
Growth
$34- Evals, prompts and agents, one place. CI/CD for engineers, collaboration for PMs.
- All platform features
- Everything in Developer
- 200,000 events included
- + €0,0005 per event
- 30 days data retention included
- + custom retention (€3/GB)
- Above 20 users: volume discount available)
- Unlimited lite-users
- Multiple users:
- Private Slack / Teams support - awesome support team!
Enterprise / Regulated
Custom- Support with on-prem or hosted deployment for high volume or privacy-sensitive data.
- Alternative hosting options; hybrid, self-hosted, on-prem
- Custom data retention
- Custom SSO / RBAC
- Audit logs
- Uptime & Support SLA
- ISO27001 reports InfoSec/legal reviews
- Custom Terms, DPA
- Forward Deployed Engineer
- Billing via AWS, Google, Azure Marketplace
Frequently asked questions
What is LangWatch?
LangWatch is an AI observability and evaluation platform for AI product teams that turns production traces into tests, simulations, and monitoring signals before release. It combines Traces, Evaluations, Agent Simulations, and Prompt Management, with Slack and HubSpot integrations plus Python, JS/TS, and OpenTelemetry support. Customers cited on the site include Booking.com and Roojoom. Plans run Developer Free, Growth $34/month, and Enterprise / Regulated custom.
How much does LangWatch cost? Is it free?
LangWatch has a free plan, with paid tiers including Growth at $34, Enterprise / Regulated at Custom.
What is LangWatch used for? Who is it for?
LangWatch is used for Traces, Evaluations, and Agent Simulations. It's built for AI engineers, Product managers, and QA and field experts.
Does LangWatch have an API and what does it integrate with?
The page advertises SDKs and integrations for Python and JS/TS, plus OpenTelemetry and framework-specific agent integrations. It integrates with OpenTelemetry, OpenAI agents, LiteLLM, DSPy, LangGraph, and 10 more.
Editor's read
Check the event and retention limits before rollout: Developer includes 50,000 events per month and 14 days of data access, while Growth includes 200,000 events and 30 days retention. If your evaluation volume or audit window exceeds that, the pricing jump is immediate.
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