Easily find and add relevant features to your ML & AI pipeline from hundreds of public, community and premium external data sources, including open & commercial LLMs

⭐️ Automatically find only relevant features that give accuracy improvement for ML model. Not just correlated with target variable
⭐️ Automated feature generation from the sources: feature generation with Large Language Models' data augmentation, RNNs, GraphNN; multiple data source ensembling
⭐️ Automatic search key augmentation from all connected sources. If you do not have all search keys in your search request, such as postal/zip code, Upgini will try to add those keys based on the provided set of search keys. This will broaden the search across all available data sources
⭐️ Calculate accuracy metrics and uplifts after enrichment existing ML model with external features
⭐️ Check the stability of accuracy gain from external data on out-of-time intervals and verification datasets. Mitigate risks of unstable external data dependencies in ML pipeline
⭐️ Easy to use - single request to enrich training dataset with all of the keys at once: date/datetime, country, postal/ZIP code, country, phone number, hashed email/HEM, IP-address
⭐️ Simple Drag & Drop Search UI:

👉 Details on datasets and features