Evidently AI: AI Evaluation and LLM Observability
Evidently AI helps AI builders and ML engineers validate model reliability. It is designed for teams that need to monitor production AI for safety risks and quality regressions.
At a glance
- Category
- Software Development
- Best for
- ML engineers, AI builders, Enterprise AI teams, Software companies building LLM apps
- Pricing
- Pricing includes free tiers for open-source and developers, with a Pro plan starting at $80/month. Enterprise pricing is custom.
- Key use cases
- RAG System Testing, Adversarial Testing, Production Model Monitoring, Multi-step Workflow Validation
- Official website
- evidentlyai.com/
Evidently AI provides a framework for testing and monitoring large language models (LLMs) and traditional machine learning systems. It is designed for software companies and enterprise teams that require a systematic evaluation process over manual spot-checks.
The platform supports various testing needs, including RAG evaluation to identify hallucinations and adversarial testing to probe for safety risks such as PII leaks. It offers an open-source Python library for local development and a managed cloud platform for team collaboration and alerting.
Buyers should confirm whether they require the no-code UI and managed hosting of the Cloud version or if the open-source library fits their technical workflow. Those with high data volumes should review the row limits associated with the different pricing tiers.
Key Features
Includes over 100 built-in metrics to measure output accuracy, safety, and quality.
Generates test inputs and adversarial scenarios to test AI resilience.
Uses external LLMs to automate the grading of AI responses based on specific criteria.
Tracks data drift and predictive quality for classifiers, recommenders, and regression models.
Identifies factually incorrect outputs and potential leaks of sensitive personal information.
Provides a library for running evaluations locally on a company's own infrastructure.
Use Cases
Evaluating retrieval quality and generation accuracy to help reduce hallucinations in chatbots.
Testing AI agents against jailbreak attempts and harmful content prompts.
Tracking distribution shifts in production data to identify model drift over time.
Testing AI agents that use tools and multi-step reasoning to validate outcomes.
Best For
Pricing
Pricing includes free tiers for open-source and developers, with a Pro plan starting at $80/month. Enterprise pricing is custom.
FAQ
It supports generative AI tasks like RAG systems and AI agents, as well as predictive AI tasks including classification and recommendation systems.
Yes, there is an open-source Python library and a free Developer plan for hobby projects and experiments.
The Pro plan costs $80/month and increases limits to 100,000 rows per month, 100 GB of snapshots, and supports up to 5 seats.
Source category: Software Development
Source subcategory: Observability Platform
