
Evidently AI provides a comprehensive AI testing and evaluation platform built on a leading open-source Python library. The platform offers automated evaluation, synthetic data generation, continuous testing, and adversarial testing to ensure AI systems, including LLMs and predictive models, are safe, reliable, and high quality. It supports over 100 built-in metrics and customizable evaluations, enabling teams to detect hallucinations, data leaks, risky outputs, and cascading errors. Evidently AI serves a broad market from startups to enterprises, offering cloud and private cloud deployment with role-based access and dedicated support. The platform is widely adopted with thousands of companies using it to monitor data drift, model performance, and AI safety risks, positioning Evidently AI as a key player in AI quality assurance and MLOps.

Evidently AI provides a comprehensive AI testing and evaluation platform built on a leading open-source Python library. The platform offers automated evaluation, synthetic data generation, continuous testing, and adversarial testing to ensure AI systems, including LLMs and predictive models, are safe, reliable, and high quality. It supports over 100 built-in metrics and customizable evaluations, enabling teams to detect hallucinations, data leaks, risky outputs, and cascading errors. Evidently AI serves a broad market from startups to enterprises, offering cloud and private cloud deployment with role-based access and dedicated support. The platform is widely adopted with thousands of companies using it to monitor data drift, model performance, and AI safety risks, positioning Evidently AI as a key player in AI quality assurance and MLOps.
What they do: Build an AI evaluation and observability platform (including LLM evaluation) on top of the open-source Evidently Python library
Founded: 2021
Founders: Elena Samuylova (Co-founder & CEO); Emeli Dral (Co-founder & CTO)
Funding: Pre-Seed; total disclosed funding 130000.00 USD; backed by investors including Y Combinator and Fly Ventures (others referenced by company)
Open-source: Evidently library (Apache-2.0); 100+ built-in metrics; extensible
AI model and LLM evaluation, testing, monitoring, and observability (including ML model monitoring and LLM-specific evaluations).
2021
130000.00 USD
“Backed by investors including Y Combinator, Fly Ventures, Runa Capital, and Nauta Capital”