Welcome to the Re:infer integration guide. This page explains the available options to get communications data in and out of Re:infer. Please follow the links to learn more about each option. Please don't hesitate to contact support if you have any questions or you need modelling your use-case.
All data upload and download options described below require users to have the necessary permissions.
Emails (Microsoft Exchange)
Microsoft Exchange mailboxes can be synced into Re:infer in real time using the Exchange integration. This can be fully managed by Re:infer with no development effort for you or deployed in your own environment. If you are already extracting emails as part of an existing data pipeline, you can sync the extracted raw emails into Re:infer via the API instead.
Salesforce data can be synced into Re:infer in real time using the Salesforce Integration, which is set up and managed by Re:infer with no development effort for you.
Any other data can be synced into Re:infer in batch or in real time via the API. Another option for batch upload is to use the Re:infer command-line tool, which is available for Linux, Mac, and Windows.
CSV files up to 128 MB can be uploaded into Re:infer by users directly in the browser.
For real-time analytics and automation use-cases we recommend using the Stream API, which allows you to iterate through verbatims in a dataset. If you are integrating Re:infer as one of the enrichment steps in a data pipeline, take a look at the Predict API routes which may also be suitable for your design.
Datasets can be exported as CSV directly in the browser; there is no size limit, but large files may take a long time to download. We recommend to apply filters before exporting to limit the size of the download and make the CSV file more convenient to work with. Another option for batch download is to use the Re:infer command-line tool (available for Linux, Mac, and Windows) or the Export API route.
The download methods discussed above will differ slightly with regards to the way they provide predicted labels and entities. Please be sure to review this comparison table to pick the method that best suits your use-case.
If you want help to get started with your automation use-case, a step-by-step tutorial using the Stream API is provided here. If you are looking to understand how to use Re:infer labels in an automation use-case, take a look at the Labels documentation.
If you are looking to understand how to use Re:infer labels in an analytics use-case, take a look at the Labels documentation