Control your LLMs like never before.

Monitor and optimize your large language models with the #1 observability platform for LLMs.

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Understand the impact of model and system changes with our test suite before you go to production.

How Arthur fits in:

  • Crafts an automated test suite from datasets with intelligent success criteria
  • Expedites the human-in-the-loop validation cycle by probing models for failure modes
  • Periodically validates models for resiliency to model changes outside their control


Prevent bad user experience and reputational impact from anomalous and malicious prompt inputs.

How Arthur fits in:

  • Provides deployment gates to identify anomalous inputs, PII leakage, toxicity, and other quality metrics
  • Learns from production performance to optimize thresholds for those quality gates


Identify and analyze user feedback and model performance problems to drive better outcomes.

How Arthur fits in:

  • Provides core token-level observability, performance dashboarding, inference debugging, and alerting
  • Collects and analyzes implicit and explicit human feedback to monitor the model’s real-world impact
  • Accelerates ability to identify and debug underperforming regions

Explore how we’re thinking about and implementing LLMs