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<title>AuraOne</title>
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<h1>AuraOne</h1>
<p>
AuraOne is a human data company for AI teams and a workflow service for
enterprises. It supplies expert judgment, speech, physical-world data
and checked workflows.
</p>
<p>
<a href="https://auraone.ai">Website</a> |
<a href="https://auraone.ai/company/facts">Company facts</a> |
<a href="https://auraone.ai/open">Open tools</a> |
<a href="https://github.com/auraoneai">GitHub</a> |
<a href="https://www.linkedin.com/company/auraonecompany/">LinkedIn</a> |
<a href="https://x.com/AuraOneLabs">X</a>
</p>
<h2>Open tools</h2>
<p>All MIT licensed.</p>
<table>
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<tr><th>Tool</th><th>What it does</th><th>Source</th></tr>
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<td>EvalKit</td>
<td>Python CLI for rubric validation and linting, deterministic scoring, reviewer agreement, judge calibration, drift and leakage checks, and evidence reports. Runs on files you own.</td>
<td><a href="https://github.com/auraoneai/open">auraoneai/open</a></td>
</tr>
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<td>rubric-spec</td>
<td>Validate, lint, diff, and convert portable AuraOne Rubric Schema v1 files.</td>
<td><a href="https://github.com/auraoneai/rubric-spec">auraoneai/rubric-spec</a></td>
</tr>
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<td>iaa-kit</td>
<td>Measure inter-annotator agreement with modern metrics, uncertainty, ordinal support, and missing-data handling.</td>
<td><a href="https://github.com/auraoneai/iaa-kit">auraoneai/iaa-kit</a></td>
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<td>judge-bench</td>
<td>Probe judge behavior for position, verbosity, self-preference, paraphrase, anchoring, and calibration failures.</td>
<td><a href="https://github.com/auraoneai/judge-bench">auraoneai/judge-bench</a></td>
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<td>lerobot-quality-gates</td>
<td>Check a LeRobot-style dataset's metadata, episodes, timestamps and video references before training or publication.</td>
<td><a href="https://github.com/auraoneai/lerobot-quality-gates">auraoneai/lerobot-quality-gates</a></td>
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<td>Rubric Studio Open</td>
<td>Author, validate, preview, calibrate, diff, and export criterion-level AI evaluation rubrics.</td>
<td><a href="https://github.com/auraoneai/rubric-studio-open">auraoneai/rubric-studio-open</a></td>
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<td>Agent Studio Open</td>
<td>Connect agent systems, inspect tool traces, replay failures, compare candidates, and export regression evidence.</td>
<td><a href="https://github.com/auraoneai/agent-studio-open">auraoneai/agent-studio-open</a></td>
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<h2>Packages</h2>
<p>
Python, on PyPI:
<a href="https://pypi.org/project/auraone-evalkit/">auraone-evalkit</a>,
<a href="https://pypi.org/project/rubric-spec/">rubric-spec</a>,
<a href="https://pypi.org/project/iaa-kit/">iaa-kit</a>,
<a href="https://pypi.org/project/judge-bench/">judge-bench</a>,
<a href="https://pypi.org/project/lerobot-quality-gates/">lerobot-quality-gates</a>.
</p>
<p>
JavaScript, on npm under the @auraone scope:
<a href="https://www.npmjs.com/package/@auraone/sdk">@auraone/sdk</a>,
<a href="https://www.npmjs.com/package/@auraone/agent-studio">@auraone/agent-studio</a>,
<a href="https://www.npmjs.com/package/@auraone/github-app">@auraone/github-app</a>,
<a href="https://www.npmjs.com/package/@auraone/aura-ide-kit">@auraone/aura-ide-kit</a>,
<a href="https://www.npmjs.com/package/@auraone/platform-contracts">@auraone/platform-contracts</a>,
<a href="https://www.npmjs.com/package/@auraone/proofline-oss">@auraone/proofline-oss</a>.
</p>
<h2>Datasets</h2>
<p>
Small synthetic tutorial datasets for the tools above. The rows are
hand-written. They are not expert-authored, not human-validated, and
not for training or benchmarking.
</p>
<ul>
<li><a href="https://huggingface.co/datasets/auraone/evalkit-tutorial-v0.1">evalkit-tutorial-v0.1</a></li>
<li><a href="https://huggingface.co/datasets/auraone/synthetic-multiturn-eval-v0.1">synthetic-multiturn-eval-v0.1</a></li>
</ul>
<p class="note">
AuraOne (auraone.ai) is a different company from Aura, the
identity-protection service at aura.com.
</p>
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