> For the complete documentation index, see [llms.txt](https://knowledge.aterio.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://knowledge.aterio.io/data-delivery-options/introduction.md). # Introduction Aterio data is built to drop into the tools and workflows your team already uses. Whether you work in a cloud data warehouse, pull data through code, or want it available to your AI tools, we deliver it in a format that fits. ### What you're working with Aterio isn't a set of flat lists. It's a connected view of the infrastructure landscape, where projects, the companies behind them, and the links between them are all mapped. • Every project shows who's behind it: developers, asset owners, investors, and parent companies, labeled by role. • Every company connects the picture, showing what it's involved in across data centers, industrial, and power generation. • Products link to each other: power generation connects to the data centers it powers, including behind-the-meter supply. • The data has history: projects carry lifecycle events and are available point-in-time, so you can see how the landscape changes. ### How access works Access to Aterio data is provisioned as part of onboarding — it is not self-serve. We scope each integration to the products you're subscribed to and set it up with you directly. This keeps your access secure and matched to your use case. If you'd like to explore the data or see how a delivery option fits your stack, the best next step is a short call. ### Which delivery option is right for you A quick guide to the option that usually fits best. If you're not sure, we'll help you pick on the call.
If you want to…Best fit
Query Aterio data next to your own, with no pipelines to runDatabases
Build a product or automate a sync on your own scheduleAPI
Make the data reachable by your AI tools and agentsMCP
Grab ready-to-use files manually, no technical setupDownload portal
*Each product can be delivered through any of the options in this section* --- # 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 dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://knowledge.aterio.io/data-delivery-options/introduction.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. 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.