Evidently AI
Open source evaluation and monitoring for ML and LLM systems with a SaaS platform offering pro and expert tiers.
Overview
Evidently provides testing and observability for machine learning and LLM applications. Teams instrument models or agents to track quality, drift and regressions using 100 plus built in metrics and visual reports. The open source library powers local testing and dashboards, while the hosted platform layers alerting, retention, multi project seats and advanced evaluations such as adversarial and synthetic data tests.
This combination suits startups and enterprises that want transparency and reproducibility without black box scoring. Typical workflows include pre deployment checks, canary rollouts with guardrails, continuous dataset drift monitoring and LLM eval harnesses that score prompts for faithfulness and safety. With clear pricing for Pro and Expert tiers, organizations can begin with hobby projects then scale to larger teams with governance and longer retention.
Key features
- Open source library with 100 plus metrics and reports
- Hosted platform with alerting and retention
- LLM evaluation harnesses and agent testing
- Synthetic and adversarial data generation options
- Multi project seats with role based access
- Drift and data quality monitoring in production
- Integrations for notebooks CI and pipelines
- Transparent dashboards to audit model health
Best for
- Run pre deployment checks and regression tests
- Monitor data drift and performance decay in prod
- Score LLM prompts for faithfulness and safety
- Set alerts for quality thresholds and anomalies
- Compare model versions during canary rollouts
- Generate synthetic cases to harden evaluations
- Share dashboards with stakeholders for decisions
- Keep historical evidence for audits and compliance
Capabilities
Metrics and reports
Use 100 plus metrics to evaluate data quality, drift and performance, then share interactive reports.
Hosted platform
Add alerting, retention and seats so teams act on issues quickly and track improvements over time.
LLM and agents
Run eval harnesses with synthetic and adversarial cases to probe safety, bias and faithfulness.
Pipelines and CI
Connect notebooks, CI and orchestration to automate checks across versions and deployments.
Frequently Asked Questions
How does pricing start?
Public pricing lists a Free tier and Pro at $50 per month with an Expert plan from $399 per month.
Is the core open source?
Yes, the library is open source and powers the hosted product, you can start locally then upgrade.
Does it support teams?
Paid tiers add seats, projects and longer retention to coordinate across orgs.
Can I monitor tabular and text models?
Yes, Evidently supports classic ML as well as LLM applications and agents.
Do you offer enterprise deployment?
Expert and enterprise engagements add advanced tests and support for private environments.
