{
  "protocolVersion": "0.3.0",
  "name": "Pioneer AI",
  "description": "Pioneer fine-tunes, evaluates, and deploys small language models. Agents can call the REST API to generate synthetic data, train models, run inference, and run evaluations.",
  "url": "https://api.pioneer.ai/",
  "supportedInterfaces": [
    {
      "url": "https://api.pioneer.ai/",
      "protocolBinding": "HTTP+JSON",
      "protocolVersion": "1.0"
    }
  ],
  "provider": {
    "organization": "Pioneer AI",
    "url": "https://pioneer.ai"
  },
  "version": "1.0.0",
  "documentationUrl": "https://docs.pioneer.ai/api-reference",
  "capabilities": {
    "streaming": true,
    "pushNotifications": false,
    "stateTransitionHistory": false
  },
  "defaultInputModes": [
    "text/plain",
    "application/json"
  ],
  "defaultOutputModes": [
    "application/json",
    "text/plain"
  ],
  "securitySchemes": {
    "apiKey": {
      "type": "apiKey",
      "in": "header",
      "name": "X-API-Key",
      "description": "Pioneer API key (prefix \"pio_sk_\")."
    },
    "bearer": {
      "type": "http",
      "scheme": "bearer",
      "bearerFormat": "JWT",
      "description": "Supabase access token issued by https://db.pioneer.ai/auth/v1."
    }
  },
  "security": [
    {
      "apiKey": []
    },
    {
      "bearer": []
    }
  ],
  "skills": [
    {
      "id": "pioneer-inference",
      "name": "Run inference",
      "description": "Run NER, classification, or text generation on a Pioneer model \u2014 native, OpenAI-compatible, or Anthropic-compatible endpoints.",
      "tags": [
        "inference",
        "ner",
        "classification",
        "generation"
      ],
      "examples": [
        "Extract people and organizations from this paragraph.",
        "Classify each support ticket as billing, technical, or other."
      ]
    },
    {
      "id": "pioneer-fine-tune",
      "name": "Fine-tune a model",
      "description": "Fine-tune a GLiNER or decoder model on a labeled dataset and monitor training until the model is ready for inference.",
      "tags": [
        "training",
        "fine-tuning",
        "lora"
      ]
    },
    {
      "id": "pioneer-synthetic-data",
      "name": "Generate synthetic training data",
      "description": "Generate synthetic NER, classification, or decoder training data with Pioneer's Felix engine, then use the dataset to start a fine-tuning job.",
      "tags": [
        "datasets",
        "synthetic-data",
        "felix"
      ]
    },
    {
      "id": "pioneer-evaluate",
      "name": "Evaluate a model",
      "description": "Evaluate a trained Pioneer model against a dataset and compare results against baseline LLMs.",
      "tags": [
        "evaluation",
        "benchmarks"
      ]
    }
  ]
}