Evidently AI
Open SourceFundedOpen-source platform for AI evaluation, monitoring, and governance
About Evidently AI
Evidently AI provides a comprehensive platform designed to evaluate, monitor, and govern AI and machine learning systems, with a particular focus on large language models (LLMs). It enables enterprises to continuously test AI quality, safety, and reliability by leveraging automated evaluation, synthetic data generation, and adversarial testing. The platform supports tracking data drift, predictive quality, and multi-step AI agent workflows, ensuring AI systems remain robust and compliant over time.
Targeted at AI builders, MLOps engineers, and data science teams within enterprises, Evidently AI addresses the unique challenges of non-deterministic AI failures such as hallucinations, data leaks, and cascading errors. Its open-source Evidently Python library underpins the platform, offering transparency and extensibility with over 100 built-in metrics. This empowers organizations to maintain AI system integrity, reduce risks, and comply with governance standards through continuous observability and actionable insights.
Key Capabilities
- ✓Automated AI output accuracy and safety evaluation
- ✓Synthetic and adversarial test case generation
- ✓Continuous monitoring of data drift and model performance
- ✓Customizable AI quality metrics and evaluation rules
- ✓LLM-specific testing including hallucination and PII detection
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