Identifood — Case study

The question

Nutrition labels are written for the literate, the unhurried, and the able-bodied. They assume good eyesight, working memory, and a tolerant relationship with small print. Identifood begins with a simpler question. If a parent could ask a calm assistant for help understanding what is on a shelf, what would the assistant actually need to do?

The shape of the system

The work is structured as a small ensemble of agents, each with a narrow responsibility, and a coordinator that holds the conversation together. The intent is restraint rather than ambition. Each agent does one thing the way a thoughtful person might do it, and the coordinator is the one who knows when to ask for clarification and when to fall quiet.

The coordinator sits at the centre and speaks to four specialist agents in turn: a vision agent that reads the photograph, a label parser that separates ingredients from nutrition facts, a reference agent that compares the result against dietary guidance the reader has shared, and a presentation agent that shapes the reply. Requests and answers pass both ways between the coordinator and each specialist; the specialists never talk to one another directly. The final agent roster and protocol diagram will be added once the system passes its second evaluation round.

Four agents, one coordinator

A vision agent reads the photograph. A label parser separates ingredients from nutrition facts. A reference agent compares the result to dietary guidance the user has previously shared. A presentation agent shapes the response into something a person can read while a child is asking a question. The coordinator asks each agent only what is needed and stops when an answer is honest enough to stand alone.

Accessibility decisions, built in

A photograph is a high barrier to entry for many users. The interface accepts a typed product name as a peer to the camera input. Returned summaries are written at an approachable reading level by default. Numerical detail is available on request rather than imposed. The response is structured so a screen reader can land on the most relevant sentence first.

The ambition is not a smarter scanner. It is a system that knows when to be quiet, and when a person would rather understand than be told.

Originality and safety

The project does not reproduce or wrap any existing nutrition application. The agent architecture, prompts, and interface are authored from a clean slate. Sample images used during development are taken in-house or sourced under permissive licenses, with documentation kept alongside the project. [placeholder] Final licensing notes will appear here once the dataset is locked.

Where it is going

A second round of evaluations is planned for spring 2026, with a small group of caretakers who manage household nutrition for family members with specific dietary needs. The case study will be updated as that work concludes.