> For the complete documentation index, see [llms.txt](https://docs.predicthq.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.predicthq.com/api/readme.md). # API reference PredictHQ provides structured, verified real-world context and demand-aware features for forecasting, ML, and AI systems. You can integrate the platform directly into production models and decision workflows. See how others are using it on our [use cases page](https://www.predicthq.com/use-cases). ## Core APIs PredictHQ offers these core APIs: * [Events API](/api/events/search-events.md) - Structured, deduplicated real-world events for grounding AI systems, explaining forecasts, and building trust in AI-driven decisions * [Features API](/api/features/get-features.md) - Pre-built, model-ready demand features aggregated from real-world events * [Forecasts API](/api/forecasts/overview.md) - Event-driven demand forecasts without building or maintaining your own model * [Beam API](/api/beam/overview.md) - Identify the real-world events that materially move your demand * [Saved Locations API](/api/saved-locations/overview.md) - Define and manage reusable business locations for consistent querying across Events, Features, Beam, and Forecasts APIs Building with AI? Start with [Build with AI](/ai/build-with-ai.md): the PredictHQ MCP server for grounded access to all of these APIs at inference time, and agent skills that teach AI coding assistants the recommended integration patterns. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.predicthq.com/api/readme.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.