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 3 APIs on the APIs.io network: Projects API, Tasks API, and Teams API. 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 12 more developer resources.
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.
If we have the wrong repository, or this product is not open source, say so on your
provider repo and we
will drop the facet rather than have you publish against it.
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 80 points between them,
because the conditional facet above carries the other
20. That is why each facet's contribution is shown against a damped
maximum: raising a quality facet moves the composite by 80% of its nominal
weight, not 100%. The full arithmetic is at apis.io/rating/.
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...
aid: surge-ai
name: Surge AI
description: 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).
type: Index
deliveryModel:
model: open-core
license: MIT
open_source: true
commercial: true
callable_host: true
label: Open core · an OSS project plus a commercial hosted product
confidence: high
source:
- license
- openapi
- pricing
generated: '2026-08-28'
method: derived
accessModel:
pricing: free
onboarding: self-serve
trial: false
try_now: true
public: false
label: Free · Self-serve signup
confidence: medium
source:
- plans
- authentication
- security
generated: '2026-09-03'
method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/surge-ai.png
tags:
- Human Data
- RLHF
- SFT
- Rubrics
- Verifiers
- RL Environments
- Multi-Modal
- Internationalization
- Labeling
tags_raw:
- Human Data
- RLHF
- SFT
- Rubrics
- Verifiers
- RL Environments
- Multimodal
- Internationalization
- Labeling
url: https://raw.githubusercontent.com/api-evangelist/surge-ai/refs/heads/main/apis.yml
created: '2026-05-23'
modified: '2026-05-23'
specificationVersion: '0.23'
apis:
- aid: surge-ai:surge-api
name: Surge API
description: 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 (create, list, retrieve individual tasks), and blueprints
(list and use as templates for new projects). Authentication uses an API key sourced from the user's Surge profile, passed
via the SURGE_API_KEY environment variable or set explicitly on the client. The reference is published in the Surge dashboard
at app.surgehq.ai/docs/api.
humanURL: https://app.surgehq.ai/docs/api
tags:
- REST API
- Project
- Task
- Blueprints
tags_raw:
- REST API
- Projects
- Tasks
- Blueprints
properties:
- type: Documentation
url: https://app.surgehq.ai/docs/api
- type: APIReference
url: https://app.surgehq.ai/docs/api
- type: Authentication
url: https://app.surgehq.ai/docs/api
- type: SDKs
url: https://github.com/surge-ai/surge-python
- aid: surge-ai:surge-python-sdk
name: Surge Python SDK
description: 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 environment variable.
humanURL: https://github.com/surge-ai/surge-python
tags:
- SDK
- Python
- Open-Source
tags_raw:
- SDK
- Python
- Open Source
properties:
- type: GitHubRepository
url: https://github.com/surge-ai/surge-python
- type: SDKs
url: https://pypi.org/project/surge-api/
- aid: surge-ai:surge-rl-environments
name: Surge RL Environments and Agents
description: Surge's product surface for delivering complex reinforcement-learning environments and agents that challenge
and evaluate agentic models.
humanURL: https://www.surgehq.ai/products
tags:
- RL Environments
- Agents
- Evals
properties:
- type: Documentation
url: https://www.surgehq.ai/products
- aid: surge-ai:surge-rubrics-verifiers
name: Surge Rubrics and Verifiers
description: Scoring rubrics and automated verifiers for grading AI outputs across domains.
humanURL: https://www.surgehq.ai/products
tags:
- Rubrics
- Verifiers
- Evals
properties:
- type: Documentation
url: https://www.surgehq.ai/products
- aid: surge-ai:surge-rlhf
name: Surge RLHF
description: Preference and reward data for reinforcement learning from human feedback.
humanURL: https://www.surgehq.ai/products
tags:
- RLHF
- Preference Data
properties:
- type: Documentation
url: https://www.surgehq.ai/products
- aid: surge-ai:surge-sft
name: Surge SFT
description: Foundational-skill demonstration data for supervised fine-tuning.
humanURL: https://www.surgehq.ai/products
tags:
- SFT
- Fine-Tuning
properties:
- type: Documentation
url: https://www.surgehq.ai/products
- aid: surge-ai:surge-human-evaluation
name: Surge Human Evaluation
description: Quality assessment of AI outputs by Surge's expert workforce.
humanURL: https://www.surgehq.ai/products
tags:
- Human Evaluation
- Quality
properties:
- type: Documentation
url: https://www.surgehq.ai/products
- aid: surge-ai:surge-multimodal
name: Surge Multimodal Data
description: Image, audio, and video data collection and labeling.
humanURL: https://www.surgehq.ai/products
tags:
- Multi-Modal
- Image
- Audio
- Video
tags_raw:
- Multimodal
- Image
- Audio
- Video
properties:
- type: Documentation
url: https://www.surgehq.ai/products
- aid: surge-ai:surge-internationalization
name: Surge Internationalization
description: Multilingual data across 70+ languages for localization, translation, and multilingual model evaluation.
humanURL: https://www.surgehq.ai/products
tags:
- Internationalization
- Multilingual
- Translation
properties:
- type: Documentation
url: https://www.surgehq.ai/products
- aid: surge-ai:surge-off-the-shelf-data
name: Surge Off-The-Shelf Data
description: Pre-built datasets ready for licensing and download.
humanURL: https://www.surgehq.ai/products
tags:
- Datasets
- Pre-Built Data
properties:
- type: Documentation
url: https://www.surgehq.ai/products
- aid: surge-ai:surge-toxicity-dataset
name: Surge Toxicity Dataset
description: The world's largest open social-media toxicity dataset, published under MIT license.
humanURL: https://github.com/surge-ai/toxicity
tags:
- Dataset
- Open Data
- Toxicity
- Trust and Safety
properties:
- type: GitHubRepository
url: https://github.com/surge-ai/toxicity
- aid: surge-ai:surge-ai-projects-api
name: Surge AI Projects API
description: The Projects API from Surge AI — 9 operation(s) for projects.
humanURL: https://app.surgehq.ai/docs/api
tags:
- Project
tags_raw:
- Projects
properties:
- type: OpenAPI
url: openapi/surge-ai-projects-api-openapi.yml
- aid: surge-ai:surge-ai-tasks-api
name: Surge AI Tasks API
description: The Tasks API from Surge AI — 5 operation(s) for tasks.
humanURL: https://app.surgehq.ai/docs/api
tags:
- Task
tags_raw:
- Tasks
properties:
- type: OpenAPI
url: openapi/surge-ai-tasks-api-openapi.yml
- aid: surge-ai:surge-ai-teams-api
name: Surge AI Teams API
description: The Teams API from Surge AI — 1 operation(s) for teams.
humanURL: https://app.surgehq.ai/docs/api
tags:
- Team
tags_raw:
- Teams
properties:
- type: OpenAPI
url: openapi/surge-ai-teams-api-openapi.yml
common:
- type: Website
url: https://www.surgehq.ai/
- type: IssueTracker
url: https://github.com/surge-ai/surge-python/issues
- type: License
name: MIT
url: https://github.com/surge-ai/surge-python/blob/main/LICENSE
- type: AgenticAccess
url: agentic-access/surge-ai-agentic-access.yml
- type: DomainSecurity
url: security/surge-ai-domain-security.yml
- type: Authentication
url: authentication/surge-ai-authentication.yml
- type: Portal
url: https://www.surgehq.ai
- type: Documentation
url: https://app.surgehq.ai/docs/api
- type: APIReference
url: https://app.surgehq.ai/docs/api
- type: Authentication
url: https://app.surgehq.ai/docs/api
- type: Signup
url: https://app.surgehq.ai/customers/sign_in
- type: Console
url: https://app.surgehq.ai
- type: SDKs
url: https://github.com/surge-ai/surge-python
name: Surge Python SDK
- type: SDKs
url: https://pypi.org/project/surge-api/
name: surge-api on PyPI
- type: GitHubOrganization
url: https://github.com/surge-ai
- type: GitHubRepository
url: https://github.com/surge-ai/toxicity
name: Surge Toxicity Dataset
- type: Blog
url: https://www.surgehq.ai/blog
- type: Support
url: https://www.surgehq.ai
- type: X
url: https://x.com/HelloSurgeAI
- type: Features
data:
- name: Surge REST API
description: Endpoints for projects, tasks, and blueprints, with API-key authentication.
- name: Python SDK
description: Official surge-python SDK on PyPI, MIT-licensed, Python 3.10+.
- name: RL Environments and Agents
description: Complex environments that challenge agentic models.
- name: Rubrics and Verifiers
description: Scoring systems for AI outputs across domains.
- name: RLHF and SFT
description: Preference, reward, and demonstration data for foundation-model training.
- name: Human Evaluation
description: Expert workforce grades AI output quality.
- name: Expert Professional Domains
description: Specialized expertise across finance, law, medicine, and more.
- name: 70+ Languages
description: Internationalization coverage spanning more than 70 languages.
- name: Multimodal Data
description: Image, audio, and video collection and labeling.
- name: Off-The-Shelf Datasets
description: Pre-built datasets available for licensing.
- name: Open Datasets
description: Public releases including the world's largest social-media toxicity dataset.
- type: UseCases
data:
- name: Frontier Model RLHF
description: Preference and reward data for reinforcement learning from human feedback.
- name: Supervised Fine-Tuning
description: Demonstration data for SFT across professional domains.
- name: Agentic Evals
description: Benchmark agents in complex RL environments with structured rubrics.
- name: Multilingual Model Evaluation
description: Evaluate model quality across 70+ languages.
- name: Trust and Safety Research
description: Use the toxicity dataset and human evaluation pipelines for trust and safety work.
- type: Integrations
data:
- name: Python SDK
description: Programmatic integration via the official surge-python SDK.
- name: API Key Authentication
description: Standard API-key auth (SURGE_API_KEY env var or programmatic configuration).
- name: Custom Project Blueprints
description: Use Surge blueprints as templates for new labeling projects.
maintainers:
- FN: Kin Lane
url: http://apievangelist.com
email: kin@apievangelist.com
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