Refuel
Refuel is an AI data-labeling and data-enrichment platform that uses LLMs to label, clean, structure, and enrich enterprise datasets. Refuel Cloud exposes a REST API where datasets, tasks, and deployed applications transform new data in realtime, and the open-source autolabel library lets teams run the same LLM labeling workflows in their own environment.
Refuel publishes 1 API on the APIs.io network: Applications API. Tagged areas include AI, LLM, Data Labeling, Data Enrichment, and Autolabel.
Refuel’s developer surface includes authentication, documentation, and 10 more developer resources.
Kin Score
APIs 2
Individual APIs this provider publishes, each with its own machine-readable definition.
Refuel Autolabel (Open Source)
Autolabel is the open-source Python library (pip install refuel-autolabel) to label, clean, and enrich text datasets with any LLM (OpenAI, Anthropic, Google, HuggingFace, vLLM, ...
Refuel Applications API
The Applications API from Refuel — 1 operation(s) for applications.
Open Collections 1
Open, tool-agnostic API collections (OpenAPI-derived and Bruno).
Refuel Cloud API
OPEN COLLECTIONPricing Plans 1
Published pricing tiers and plan structures.
Rate Limits 1
Documented rate limits and quota policies.
Refuel Ai Rate Limits
RATE LIMITSFinOps 1
Cost, billing, and metering signals for API financial operations.
Refuel Ai Finops
FINOPSSecurity Posture 4
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Agentic Access 1
Recommended x-agentic-access execution contracts for AI agents.
Resources
Documentation 1
Reference material describing how the API behaves
Agent Surfaces 1
MCP servers, agent skills, and machine-readable catalogs
Build 1
SDKs, sample code, and the tooling you integrate with
Access & Security 4
Authentication, authorization, and security posture
Operate 1
Status, limits, changes, and where to get help
Commercial 2
Pricing, plans, and the legal terms of use
Company 2
The organization behind the API