Overview

Docs, guides, and API references to help you build with PredictHQ.

Everything you need to integrate PredictHQ into your models, pipelines, and AI systems.

API Quickstart API Reference

Core APIs

• Events API - Structured, deduplicated real-world events for discovery, explainability, and building trust in AI-driven decisions
• Features API - Pre-built, model-ready demand features aggregated from real-world events
• Forecasts API - Event-driven demand forecasts without building or maintaining your own model
• Beam API - Identify the real-world events that materially move your demand
• Saved Locations API - Define and manage reusable business locations for consistent querying across Events, Features, Beam, and Forecasts APIs

How It Fits Together

Start with How to use PredictHQ - the recommended integration paths by job, from model training to grounding AI systems. PredictHQ APIs work as a pipeline, not in isolation: the Standard integration pattern shows the recommended production architecture, from location setup through to forecasting and explainability.

Example

Use your Beam Analysis ID to pull model-ready ML features for any date range - location, filters, and feature selection are applied automatically.

import requests

response = requests.post(
    url="https://api.predicthq.com/v1/features/",
    headers={
        "Authorization": "Bearer $API_TOKEN",
        "Accept": "application/json"
    },
    json={
        "beam": {
            "analysis_id": "$ANALYSIS_ID"
        },
        "active": {
            "gte": "2026-06-01",
            "lte": "2026-06-30"
        }
    }
)

print(response.json())

AI & Agents

• Build with AI - Connect any MCP-compatible AI assistant to PredictHQ APIs through natural language
• MCP server - Query events, demand intelligence, and all PredictHQ APIs without writing code
• Bolt - AI-native developer environment built into the WebApp

Resources

• API Overview - Authentication, rate limits, and API conventions
• Guides - Step-by-step integration guides for core APIs and use cases
• Python SDK - The official Python client for the PredictHQ API
• Data science notebooks - Jupyter notebooks for Beam, Features API, and demand forecasting
• System Status - Live status and incident history for PredictHQ services