Integrate.ai Documentation¶
Welcome to integrate.ai
Revolutionize Your Data Strategy: Evaluate Third-Party Data in Minutes, Not Months
The demand for high-quality third-party data to fuel AI and advanced models is soaring, yet the traditional evaluation process is slow, cumbersome, and fraught with data-sharing risks, often taking over a year. Integrate.ai solves this fundamental challenge by pioneering a new paradigm for data evaluation: one that enables you to explore and test external data and models without sharing sensitive record-level information. Leveraging cutting-edge Federated Learning and privacy-preserving technologies, our system allows data to remain secure with its owners while you gain critical analytical insights. This dramatic shift eliminates lengthy data-sharing negotiations, slashing the time from initial engagement to a confident investment decision.
The integrate.ai platform is built around three core, privacy-enabled functions: Discover relevant datasets, Explore content and properties, and Test value against specific targets.
For data science and actuarial teams seeking deep technical analysis, the Python SDK is the code-level native interface. It empowers data scientists with a familiar notebook environment to perform deep exploration, modelling, and backtesting. Crucially, the SDK allows for the privacy-protected joining of your internal data with provider data, enabling deep correlation analysis and robust model building across a broad range of model types—all without ever exposing a single record. With integrate.ai, you gain the speed, security, and insight required to accelerate innovation and unlock better business outcomes from external data.
Learn about our approach for data evaluation.
Get started with integrate.ai in four easy steps.
Learn about vertical and horizontal federated learning models.
Explore different techniques for data analysis.
Learn how to use the transform session and other tools.
Updated for each release.