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AI security

LangWatch ✓

Simulation-based AI agent testing and evaluation that turns unpredictable agents into reliable

Source rating 5.0 (3) 6.5k views 49 saves 1 comments Paid
Agent Evaluations Agent Governance Agent Simulations
More categories (4)
API Claude Code Spend DSPy AI security
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from $29/mo

Verdict

A quick read before you dig into the full page.

Best if
You are aI Engineers and need: Identify, debug, and resolve blindspots in AI stacks
Skip if
May have learning curve
Pick this when
Agent Simulations

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Overview

"LangWatch is the open-source (Apache-2.0) platform for teams shipping AI agents to production. Agent simulations test multi-turn and voice agents before release: a user simulator drives realistic conversations while a judge agent scores every turn, running locally, in CI, or no-code.

In production, the same evaluators score live traffic in real time, guardrails protect against PII leaks and prompt injection, and OpenTelemetry-native tracing makes multi-agent systems legible.

An AI gateway governs every model, key, and tool across the organization. Self-hosted, hybrid, or cloud (EU/US/UK/APAC), ISO 27001 certified and GDPR compliant.

Built in Amsterdam, trusted by enterprises in banking and payments including Deloitte, Backbase, and PagBank."

LangWatch website

Best for

Short scenarios where LangWatch tends to shine.

  • Identify, debug, and resolve blindspots in AI stacks.

    Best for AI Engineers

  • Integrate automated LLM evaluations directly into workflows.

    Best for AI Architects

  • Keep AI reliable and under control with real-time monitoring.

    Best for AI Researchers

  • Improve data with human-in-the-loop workflows for annotations and labeling.

    Best for Data Scientists

  • Automatically find the best prompt and few shot examples for the LLMs.

    Best for MLOps Engineers

Example outputs 1

Sample generations and before/after results for LangWatch.

LangWatch screenshot
LangWatch screenshot LangWatch website

Access & connections

Where you can use LangWatch, and what it plugs into.

Platforms

Web

Integrations

MCP

API

Public API available

Browse other tools with an API

Capabilities

What this tool accepts, produces, and is strongest at.

Input

  • API
  • Tabular
  • Image
  • Video
  • Audio

Output

  • API
  • Text

Highlights

  • Agents
  • API
  • MCP
  • No Signup
  • Open Source
  • Local

Supported features

  • Agents
  • API
  • MCP
  • No Signup
  • Open Source
  • Runs Locally

Pros & cons

Pros

  • Agent Simulations
  • Speeds up quality assurance
  • Agent evaluations
  • Stanfords DSPy framework integration
  • LLM observability
  • AI agent Governance
  • Claude code usage / spend
  • Continual progress stimulation
Show 31 more
  • Reduces manual work
  • Applicable to various fields
  • Measurable quality, assurance, latency, cost
  • Message and output debugging
  • Keeps track of versioned experiments
  • Facilitates full dataset management
  • Compatible with all LLM models
  • Tracks optimization progress visually
  • One-click LLM performance optimization
  • Prompt discovery
  • Auto-optimization
  • Legal, sales, customer service tools
  • Healthcare and financial analysis
  • Latency reduction
  • Allows domain experts involvement
  • Enterprise-grade controls
  • Self-hosted deployment
  • GDPR compliant
  • Role-based access controls
  • Custom models integration
  • API-accessible tools integration
  • Datasets and cost tracking
  • Annotations
  • Topic, events, custom graph analytics
  • Jailbreak detection
  • Optimization studio integration
  • Supports all LLMs
  • Features chain of thought prompting technique
  • Structured vibe-checking
  • Safety and compliance tools
  • Performance measurement tools

Cons

  • No mention of mobile support
  • Potential privacy issues (domain experts)
  • Uncertain compatibility with non-LLM models
  • No built-in app integration
  • May have learning curve

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Releases 1

Initial release January 2, 2025 Current
Initial release of LangWatch.

Imported reviews 1

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Manouk Draisma Jan 2, 2025 v@ initial release

Best LLMops tool in the market.

FAQ 12

What is the primary function of LangWatch?
LangWatch's primary function is to optimize Language Model applications (LLMs). It leverages Stanford's DSPy framework to automatically discover the best prompts and models, replacing manual work and quickening the process significantly. LangWatch's functionalities aim to smooth out quality assurance and hasten the rate of shipping by providing features like intuitive analytics dashboards, model discovery, auto-optimization, debugging, versioned experiments, and full dataset management.
Can LangWatch be used for various fields like Legal, Sales, Health etc?
Yes, LangWatch is not just designed for developers. It accommodates domain experts from various fields including Legal, Sales, Customer Services, HR, Health, and Finance to be actively involved in the process, enabling a wider scope of application.
What is the DSPy framework in LangWatch?
LangWatch's DSPy framework, developed by Stanford, aids in the automatic discovery of the best prompts and models. It ensures seamless optimization of LLMs and is a critical component in LangWatch's operational scheme as it aids in quickening manual work involved in prompt and model selection.
Does LangWatch support all LLM models and optimizers?
Yes, LangWatch exhibits full compatibility with all LLM models and optimizers including the DSPy framework. This offers flexibility and versatility to LangWatch users by allowing them to switch and adjust their LLM models as per requirements.
How does the drag and drop feature of LangWatch enhance collaboration?
LangWatch's drag and drop feature acts as a powerful tool for team collaboration. It simplifies the process of shared working spaces, allowing users to easily manage, share, and work together on different aspects of LLM optimization, enhancing overall project productivity.
What is the role of the analytics dashboard in LangWatch?
The analytics dashboard in LangWatch serves as an intuitive tool for project monitoring and evaluation. It provides vital insights related to system performance, model efficiency, and progress tracking. The dashboard's comprehensive data view aids in making informed decisions and guiding optimization efforts.
How does LangWatch help in reducing latency?
LangWatch contributes to latency reduction by automating many manual tasks involved in optimizing LLMs. This includes automatically discovering the best prompts and models, which significantly speeds up the process, thereby reducing latency.
What is the purpose of versioned experiments in LangWatch?
Versioned experiments in LangWatch are instrumental in recording and tracking the performance of various pipelines, prompts, and models. This offers a historical perspective on best performers and facilitates comparative analysis, which is crucial in continuous improvement and progress.
Does LangWatch allow debugging of messages and outputs?
Yes, LangWatch allows debugging of messages and outputs. This feature enables users to identify and rectify any performance issues or errors, ensuring smooth functioning of their LLM applications.
How is manual work reduced with LangWatch?
LangWatch significantly reduces manual work by automating critical parts of LLM optimization process. It automatically finds the best prompt or model, which typically requires a lot of manual tweaking and experimentation. The use of the DSPy framework allows the same quality of outcomes but in a fraction of the standard time.
How does LangWatch ensure quality assurance?
LangWatch ensures quality assurance by incorporating a scientific approach to measure LLM quality. All aspects including quality, latency, and costs are quantifiable metrics within the LangWatch system. Concept of versioned experiments and full dataset management also plays a vital role in maintaining high quality standards.
What does LangWatch offer for dataset management?
LangWatch offers full dataset management that facilitates collaboration and sets quality standards. As part of dataset management, users can collaborate, share and establish quality indicators for their datasets, making the process more systematic and organized.
LangWatch from $29/mo
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