Tastev3.0.1

A food delivery or dining app uses Taste to scan user emails for restaurant bookings and delivery orders, then recommends new venues based on actual consumption history. Users get evidence-backed suggestions that explain why a place matches their taste.

A travel booking platform leverages Taste's email and calendar scanning to identify past hotel stays and travel bookings. It then recommends new destinations or accommodations that align with the user's preferences, citing prior trips.

A streaming service integrates Taste to analyze user purchase confirmations for movies, music, or shows. It generates cross-domain recommendations, e.g., suggesting a documentary similar to a previously watched film, with references to the specific prior consumption.

An e-commerce platform uses Taste to automatically extract purchase signals from email receipts and calendar events (e.g., upcoming birthday). It then suggests complementary or similar products, avoiding items already bought, and explains the recommendation based on past purchases.

A fitness app connects to Taste to scan calendar bookings for gym sessions, yoga classes, or spa appointments. It recommends new studios or classes with similar vibes or intensity levels, citing the user's past attendance history.

Offer Taste as an add-on service for subscription-based platforms (e.g., meal kits, streaming services) to provide hyper-personalized recommendations. Revenue comes from a monthly fee per user or a tiered subscription for access to the taste modeling feature.

License the Taste engine to retailers, travel agencies, and hospitality companies as a white-label API. They integrate it into their systems for evidence-based recommendations, and you charge per API call or a fixed monthly licensing fee.

Aggregate anonymized taste patterns from user consent to sell periodic trend reports to brands, advertisers, and market researchers. For example, a report on emerging cuisine preferences or popular venue types in a region.