Food labels should be easier to use.

Barcode scanning is Ingrediensia's primary and recommended path. Ingrediensia separates ingredients into natural, processed, artificial, and genuinely unclassified groups; explains recognized ingredients; and presents nutrition, dietary, processing, and optional health-priority indicators together.

When a barcode is not available in the product sources, an experimental camera workflow can read ingredient and Nutrition Facts panels. Camera text recognition can make mistakes, so users review the extracted text before analysis.

The score is a comparison aid, not a verdict. Its rules and version are disclosed so you can understand the result and make your own purchase decision.

The app combines package-label OCR with openly reusable product data, a conservative ingredient ontology, and deterministic scoring. It keeps uncertain classifications visible instead of inventing an answer, and it distinguishes source facts from Ingrediensia's own analysis.

No account is required. Recent scans, health priorities, and optional coarse location preferences are stored in your browser. See the Privacy and Sources pages for the complete details and limitations.

I'm Shloka Mhaisekar, the creator of Ingrediensia. I built this project to explore how technology can make packaged-food information clearer and more useful for families. You can follow my work on LinkedIn. Ingrediensia began as a practical way to make packaged-food choices more understandable without pretending to replace a package label or qualified medical advice.