Evidently AI
by Evidently AI
At a glance
Python evaluation framework for monitoring data quality, predictive models and LLM applications.
eval developer-tools
- Licence
- Not recorded
- Category
- Platforms & Infrastructure
- Business model
- Open (open weights/source)
- Availability
- Not recorded
- Launched
- Not recorded
Overview
Typical uses include Investigation of agent failures; Regression evaluation of AI applications. Documented capabilities: Evaluate data and AI systems using a Python metric library; Detect data drift and predictive quality issues; Self-hosted testing dashboards and evaluation storage.
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Key features
- Evaluate data and AI systems using a Python metric library
- Detect data drift and predictive quality issues
- Self-hosted testing dashboards and evaluation storage
Use cases
- Investigation of agent failures
- Regression evaluation of AI applications
Pricing
The open-source software can be run on your own infrastructure. Compute, storage and any external model API usage are separate costs; a managed service is not included.
Record details
Provenance, dates and links are kept here so the main sections stay about the product itself.
Links, dates and provenance
- Record updated
- 2026-11-03
- Documentation
- docs.evidentlyai.com ↗
Selection profile
Every field says where its value comes from. "Unknown" means we have not confirmed it — it does not mean the product lacks the feature.
Selection profile11 fields7 unknown
- Tasks it fits
- Data analysis
Editorial classification of the documented features; not a product-performance test.
Suggest a correction - How you use it
- Library
Editorial classification of the documented features; not a product-performance test.
Suggest a correction - Runs on
- Not recorded
This product-specific field was not established in this entry’s source review.
Suggest a correction - Where it runs
- Self-hosted
Editorial classification of the documented features; not a product-performance test.
Suggest a correction - Works offline
- Not recorded
This product-specific field was not established in this entry’s source review.
Suggest a correction - Official service region
- Not recorded
This product-specific field was not established in this entry’s source review.
Suggest a correction - Public API
- Not recorded
This product-specific field was not established in this entry’s source review.
Suggest a correction - Licence
- Not recorded
This product-specific field was not established in this entry’s source review.
Suggest a correction - Commercial use
- Not recorded
This product-specific field was not established in this entry’s source review.
Suggest a correction - Interface languages
- Not recorded
This product-specific field was not established in this entry’s source review.
Suggest a correction - Billing
- Open source Free allowance: Yes Subscription required: No
Prices are the vendor’s advertised entry price and exclude taxes; always confirm on the vendor’s own page.
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Where each value comes from
- Tasks it fits
- Our inference
- How you use it
- Our inference
- Runs on
- Unknown
- Where it runs
- Our inference
- Works offline
- Unknown
- Official service region
- Unknown
- Public API
- Unknown
- Licence
- Unknown
- Commercial use
- Unknown
- Interface languages
- Unknown
Key facts and their evidence
Each fact lists the conditions it holds under, the page it was read from and the day it was checked.
-
Capability: Evaluate data and AI systems using a Python metric library Verified 2026-11-03 docs.evidentlyai.com ↗
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Frequently asked questions
Where does Evidently AI fit in a workflow?
Python evaluation framework for monitoring data quality, predictive models and LLM applications. Evaluate data and AI systems using a Python metric library.
What costs and limits should I compare before choosing Evidently AI?
The open-source software can be run on your own infrastructure. Compute, storage and any external model API usage are separate costs; a managed service is not included.
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Sources
This record was last reviewed on 2026-11-03.
Machine-readable record: /api/products/evidently-ai.json · Spot an error? Suggest a correction