# Surge AI

**Canonical:** https://apis.io/providers/surge-ai/  
**Website:** https://www.surgehq.ai  
**APIs profiled:** 14

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).

## Kin Score — 42.5 / 100 (developing)

Scored 2026-08-25 under rubric 0.14.0. Trend: flat (+0.0 from 42.5).

| Facet | Score |
|---|---|
| Discoverability | 64.8 |
| Contract Quality | 50.3 |
| Governance | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 23.7 |
| Developer Ergonomics | 59.5 |
| Commercial Clarity | 42.1 |
| Access Clarity | 42.1 |

## Agent readiness — 21.5 (agent-aware)

| Dimension | Value |
|---|---|
| Spec Presence | yes |
| Agentic Access | derived |
| Reversibility Documented | documented |
| MCP Server | no |
| Auth Clarity | bearer |
| Idempotency | no |
| Error Semantics | no |
| OpenAPI Examples | no |
| Rate Limit Signal | documented |
| Event Surface Described | no |
| Agent Skills | no |
| Well Known Catalog | no |
| Consent Identity | no |
| Agent Card | no |
| Dry Run Mode | no |
| Delegated Identity | no |
| Protected Resource Metadata | no |
| Dynamic Client Registration | no |
| Agentic Commerce | no |

## Access

Free · Self-serve signup — onboarding: self-serve, pricing: free, trial: no (confidence: high).

## APIs (14)

- **Surge API** — 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...
- **Surge Python SDK** — 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...
- **Surge RL Environments and Agents** — Surge's product surface for delivering complex reinforcement-learning environments and agents that challenge and evaluate agentic models.
- **Surge Rubrics and Verifiers** — Scoring rubrics and automated verifiers for grading AI outputs across domains.
- **Surge RLHF** — Preference and reward data for reinforcement learning from human feedback.
- **Surge SFT** — Foundational-skill demonstration data for supervised fine-tuning.
- **Surge Human Evaluation** — Quality assessment of AI outputs by Surge's expert workforce.
- **Surge Multimodal Data** — Image, audio, and video data collection and labeling.
- **Surge Internationalization** — Multilingual data across 70+ languages for localization, translation, and multilingual model evaluation.
- **Surge Off-The-Shelf Data** — Pre-built datasets ready for licensing and download.
- **Surge Toxicity Dataset** — The world's largest open social-media toxicity dataset, published under MIT license.
- **Surge AI Projects API** — The Projects API from Surge AI — 9 operation(s) for projects.
- **Surge AI Tasks API** — The Tasks API from Surge AI — 5 operation(s) for tasks.
- **Surge AI Teams API** — The Teams API from Surge AI — 1 operation(s) for teams.

## Agentic access (1)

- **Surge Ai Agentic Access** — 18 operations · 10 acting

## Security (2)

- **Surge Ai Authentication** — http · 1 scheme
- **Surge Ai Domain Security** — TLSv1.3 · DMARC

## Plans (1)

- **Surge Ai Plans Pricing**

## Use cases (5)

- **Frontier Model RLHF** — Preference and reward data for reinforcement learning from human feedback.
- **Supervised Fine-Tuning** — Demonstration data for SFT across professional domains.
- **Agentic Evals** — Benchmark agents in complex RL environments with structured rubrics.
- **Multilingual Model Evaluation** — Evaluate model quality across 70+ languages.
- **Trust and Safety Research** — Use the toxicity dataset and human evaluation pipelines for trust and safety work.

## Tags

Human Data, RLHF, SFT, Rubrics, Verifiers, RL Environments, Multi-Modal, Internationalization, Labeling

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Profiled by [API Evangelist](https://apievangelist.com) and published on [APIs.io](https://apis.io/providers/surge-ai/). Scores are computed from the provider's own public artifacts under a published rubric.