Savora

Savora treats the fridge as the starting point of meal planning. A vision model reads what is already inside, a generative recipe engine turns those ingredients into meals that fit the household's taste profile and time budget, and a voice-first cook-along mode keeps hands free at the stove. Around that core, a pantry radar surfaces what needs eating first, and a weekly planner converts the plan into a synchronized grocery list so shopping fills gaps instead of creating surplus. The concept is designed mobile-first: every screen is a phone screen, photographed in the kitchens and pantries where the product lives, with the Savora brand carried by the environment as much as by the interface.

Most recipe apps start from a database of dishes and ask shoppers to buy towards them, which is why ingredients die at the back of the fridge. A useful kitchen companion has to work in the opposite direction: read what exists, respect dietary constraints and time, and only then suggest what to cook or buy. That inversion makes computer vision, generation, sequencing and voice interaction one connected problem rather than four separate features, and it has to hold together on a small screen used with wet hands in a warm, bright, messy room.

Savora opens with a scan: one photo of the open fridge becomes a tracked inventory with confidence scores. The recipe studio then generates dishes from that inventory, explaining which expiring items each dish rescues and offering substitutions when something is missing. Cook-along takes over at the stove with large timers and a voice loop, while the pantry radar keeps a running use-it-first queue between sessions. The weekly plan closes the loop, laying seven days of meals over the household taste profile and diffing the plan against the tracked inventory to produce a gap-only grocery list synced to the store app. Flutter keeps iOS and Android parity, with FastAPI services, PostgreSQL and Redis behind the vision, generation and planning pipelines.