Surge AI is a human-data company that provides large-scale, expert-quality labeled data for training and evaluating frontier AI models. The product surface spans RL environments and agents (rich, complex environments that challenge agentic models), rubrics and verifiers (scoring systems for AI outputs), RLHF (preference and reward data), SFT (foundational skill demonstrations), human evaluation, expert professional domains, internationalization across 70+ languages, multimodal (image, audio, video) data, and off-the-shelf datasets. Surge ships an official Python SDK (surge-python) wrapping the Surge API, with API-key authentication, and exposes the dashboard and API reference at app.surgehq.ai. Public datasets published by Surge include the toxicity dataset (the world's largest social-media toxicity dataset).
Surge AI publishes 14 API contracts indexed on the APIs.io network, including Projects API, Tasks API, Teams API, and 11 more. Tagged areas include Human Data, RLHF, SFT, Rubrics, and Verifiers.
Surge AI’s developer surface includes authentication, developer portal, documentation, API reference, signup flow, developer console, engineering blog, and 15 more developer resources.
Regulatory Posture applies to this provider. Its tags matched the
AI & Biometrics regime, so
Regulatory Posture carries 15 points of the composite.
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Open Source Surface applies to this provider. This product is open source and we
read its repository directly, so Open Source Surface carries
10 points of the composite. It is scored from what the repository actually
publishes — a security policy, a contribution guide, a release history, a code of conduct — read live from the
provider rather than inferred from our own catalog pointers.
This facet adds; nothing was taken away to make room for it. An open-source project is not excused from
the commercial facets, because exemption would strip it of the points it does earn.
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Create-or-Update Ergonomics applies to this provider. This API accepts writes, so it
carries 10 points of the composite. It is scored from the published contracts
themselves: whether a caller can create-or-update in one call, whether the write accepts a key the caller already
holds, and whether the response says which branch ran. Without that, every write needs a search-and-branch in
front of it, and the first time that check is skipped a duplicate record is created.
Scored against the observed mean rather than raw — a provider at the catalog average is unchanged by this facet,
not penalised by it.
The six quality facets above are damped to 65 points between them,
because both conditional facets apply and carry
35 points together. That is why each facet's contribution is shown against a damped
maximum: raising a quality facet moves the composite by 65% of its nominal
weight, not 100%. The full arithmetic is at apis.io/rating/.
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Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. Every facet and dimension name above is a link: it opens that measurement's own page — what it means, the exact checks that feed it, how the whole catalog distributes on it, and the providers at the top of it. This rating is computed from github.com/api-evangelist/surge-ai: open an issue to ask a question, or submit a pull request to add artifacts.
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Surge's REST API for managing labeling projects, tasks, and results. Endpoints cover projects (list, retrieve, create, download results, save reports in multiple formats), tasks...
Official Python SDK (surge-api on PyPI) wrapping the Surge API. Requires Python 3.10+, MIT-licensed, and last updated May 2026. Configured via surge.api_key or the SURGE_API_KEY...
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