Working with Microsoft 365’s new Copilot APIs

You can use the API to build AI applications without adding complexity; there’s no need for vector indexes or a separate query environment. Instead, you build on Microsoft’s own semantic index, which powers the enterprise search features built into the platform. This reduces the workload needed to build RAG connections, so you can concentrate on the content you want to surface in your applications without having to spend time thinking about nearest-neighbor search algorithms.

By building on the Microsoft Graph’s SharePoint heritage, you’re able to quickly surface relevant content, reducing the risk of generating hallucinations and errors by focusing operations on specific content and in specific domains. An AI application for the legal team can build on data in the libraries and lists they use, while the sales team will be able to work with historical bids and terms.

Like other Microsoft Graph calls, the retrieval API uses HTTP calls with requests embedded in the JSON body of a POST. This includes a query string of up to 1,500 characters, a list of SharePoint or connector data sources, as well as Kusto Query Language (KQL) format filters, and the required number of results. Filters are a powerful tool to choose documents with specific metadata, for example, from a single author or associated with a specific project or customer. Filter expressions use KQL and work with any document property.