Food tracking should not make the user do all the work.
ForkYa! was built around a simple idea: make the first log fast, then make the review clear enough that the data is worth using.
AI gets the log started. The database keeps it grounded.
Most tracking apps ask users to search, pick serving sizes, correct bad matches, and repeat the same steps every day. Pure photo recognition has the opposite problem: it can feel fast, but users still need a way to validate what was captured.
ForkYa! is built for the middle ground. A photo or description should get the meal moving quickly, while barcode lookup, nutrition label scanning, search, saved meals, and a food database of more than 4 million items help users review the result before it becomes coaching context.
- Fast entry for real meals, not perfect inputs.
- Database, barcode, and label tools when the facts matter.
- Editable logs that make Coach more useful later.
Better awareness, not fake precision.
The goal is not to pretend every meal can be known perfectly from a photo. The goal is to make tracking easier to keep doing, give users clear places to correct the estimate, and turn a reviewed log into practical nutrition guidance.
Built for repeat use.
ForkYa! focuses on the pieces that keep people consistent: quick capture, natural context, database-backed review, daily calories and macros, food quality signals, and coaching that can refer to the logs users already saved.