Two people, one scan, two different answers

Scan the same granola bar as a friend without any profile active and you'll both see the same base score. Turn on a Celiac profile and scan it again, and a gluten-containing ingredient can flip your personal verdict to avoid — even though the generic score didn't move.

That split is deliberate. A single number can't tell you whether a product is right for your body; it can only tell you how the product looks in general. Ingredo.app shows both numbers, side by side, with the reasoning behind each one visible.

Stage one: the base score

For food, the base score is mostly about the ingredient list: ingredient quality (weighted toward the first ingredients), processing level (NOVA), additives and organic status. Nutri-Score only nudges it, and a product with no ingredient list is not rated at all.

For cosmetics, a product starts at 100 and loses points for ingredients of concern — fragrance allergens, sulfate cleansers, parabens, known contact allergens — with a limit per kind. MI/MCI preservatives and formaldehyde releasers cap the score outright, and rinse-off products like shampoo count each concern at half weight.

Unknown ingredients are never guessed at — they're shown as unrecognised, never as a pass. If an offline AI enrichment step proposed a tag rather than a verified source confirming it, the score is marked AI-influenced with the contributing estimates listed for you to inspect.

Stage two: your personal verdict

Your profile is the set of condition and diet modules you've turned on — Celiac, Low-FODMAP for IBS, lactose intolerance, vegan, nut allergy, sensitive skin, fragrance allergy, acne-prone. Each active module reacts to specific ingredient tags.

Every tag maps to one of three flags: avoid (a hard block — gluten for a Celiac profile), caution (a soft penalty — high-FODMAP ingredients for IBS), or good match. Hard blocks come only from verified tags — our cited knowledge base, or an AI proposal confirmed by at least three independent authoritative sources; an unverified AI estimate can never set one.

A worked example: a wheat-based snack bar

With a Celiac profile active, the same bar produces three different flags depending on what a given ingredient tag says.

A second example: a shampoo

Take a shampoo whose label lists ammonium lauryl sulfate, cocamidopropyl betaine, fragrance and five fragrance allergens — linalool, limonene, citronellol, carvone and hexyl cinnamal. Its base score is 76: fragrance allergens −13, the sulfate cleanser −5, fragrance −3 and cocamidopropyl betaine −3. It is recognised as rinse-off from its ingredients, so each concern counts at half weight.

With no profile active, that is a reasonable choice. Turn on Fragrance allergy and linalool alone makes it a hard avoid — the same scan, a different answer, and the ingredient that decided it named on screen.