AIDRIN – AI Data Readiness Infrastructure
AIDRIN (AI Data Readiness Infrastructure) is a lightweight, open-source tool designed to evaluate the readiness of datasets for AI and machine learning workflows. It assesses dataset quality, completeness, and structure through quantitative metrics, across six dimensions of data readiness.
There are four ways to use it:
- Web interface: an interactive dashboard, hosted at aidrin.org or self-hosted.
- Command line:
aidrin data-quality data.csvand friends, for pipelines and CI. Includes an agentic evaluation component for domain-aware question answering and remediation. - Python library:
pip install aidrin, for notebooks and scripts. - Claude Code: an MCP server (
aidrin-mcp) and skill, to assess datasets in plain language.
For installation, usage, and contribution guidelines, please refer to the AIDRIN documentation.
Please read our Code of Conduct before contributing.
Release files for aidrin 2026.9.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| aidrin-2026.9.1.tar.gz | 219.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| aidrin-2026.9.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 478.0 kB
Release files / aidrin-2026.9.1.tar.gz
| Download URL | aidrin-2026.9.1.tar.gz |
|---|---|
| Size | 219.6 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.11.15
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Release files / aidrin-2026.9.1-py3-none-any.whl
| Download URL | aidrin-2026.9.1-py3-none-any.whl |
|---|---|
| Size | 258.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.11.15
|
