How We Use AI

Exactly which parts of our data are generated by AI, which aren't, and how we mark them.

Last Updated: July 26, 2026 · Our disclosure under Article 50 of the EU AI Act

The Short Version

Foodashi recipes and recipe photography are generated by artificial intelligence. We do not hide this, we mark it in the data itself, and we tell you exactly which parts of a response are AI-generated and which are not.

We think that distinction matters. A lot of "AI recipe" products present everything as equally trustworthy. Ours isn't, and pretending otherwise would make the genuinely reliable parts of our data less useful to you. So this page is deliberately specific.

Not everything is AI-generated. Our nutrition figures are computed from a structured ingredient database, not invented by a language model. See the breakdown below.

What Is and Isn't AI-Generated

Every recipe response carries a provenance object describing the origin of each part. Here is what those values mean:

Part of the response	Origin	What that means
Title, description, steps	AI-generated	Written by a large language model from a structured prompt. No human authored or editorially reviewed the text.
Ingredient list	AI + database	The model proposes ingredients and quantities; each one is then matched deterministically against our canonical ingredient database. Names and gram weights you receive come from that database, not free text.
Nutrition figures	Database-computed	Calculated by aggregating per-ingredient nutrient values from our canonical database. Not generated by a language model. Confidence is reported per recipe (see below).
Allergens & dietary tags	Database-derived	Derived from the resolved canonical ingredients using deterministic rules, then cross-checked. Still requires your own verification — see the safety notice.
Recipe photography	AI-generated	Rendered by a text-to-image model. These are not photographs of real dishes and do not depict real people, places or events.
Meal plans	AI-generated	The plan structure is generated by a language model. Meals that match a catalogue recipe are substituted in; any that don't are model suggestions.
Barcode product data	Third-party	Sourced from Open Food Facts, not AI-generated. See our Data Sources page.

On nutrition confidence. Where an ingredient has an authoritative measured value (for example from USDA reference data) we record full confidence. Where no authoritative value exists, the figure is AI-estimated and recorded at reduced confidence. The aggregate is exposed on each recipe as nutrition_metadata.confidence. We would rather show you a confidence score than round it up to a promise we can't keep.

How We Mark AI-Generated Content

Under Article 50(2) of the EU AI Act (Regulation 2024/1689), the outputs of a generative AI system must be marked in a machine-readable format and be detectable as artificially generated. We do this in two places, because a flag in a JSON response does not travel with an image file after you download it.

In API responses

Every response that carries recipe content includes an ai_generated flag. Full recipe responses additionally include the provenance breakdown:

// GET /api/v1/recipes/{id} { "title": "Boeuf Bourguignon", // ... "ai_generated": true, "provenance": { "text": "ai_generated", "ingredients": "ai_generated_db_resolved", "nutrition": "database_computed", "image": "ai_generated" } }

The ai_generated flag is present on full recipes, browse cards, comparison results and meal plans. It is never removed by field projection or by your plan tier — if you receive AI-generated content from us, you receive the marker with it.

In image files

Recipe images carry the marking embedded inside the file, so it survives download and redistribution. We write the IPTC standard term for generative-AI provenance into the image metadata:

Iptc4xmpExt:DigitalSourceType = http://cv.iptc.org/newscodes/digitalsourcetype/trainedAlgorithmicMedia

This is the same controlled-vocabulary term used across the industry, so our images are detectable by standard metadata tooling. We do not place visible watermarks on images. The AI Act requires machine-readable marking, not defaced pixels.

Images generated before 26 July 2026 predate our embedded-metadata implementation and may not carry the IPTC term in the file. The ai_generated flag in the API response covers them, and images are re-marked as they are regenerated. We would rather tell you this than let you assume a guarantee we can't yet make for the whole back catalogue.

If You Republish Our Content

If you display Foodashi content to your own users, the AI Act may place obligations on you as a deployer, separately from ours as a provider. We give you the markers so you can meet them; we can't meet them on your behalf.

Preserve the markers. Don't strip ai_generated or provenance from data you pass downstream, and don't re-encode our images in a way that discards their metadata.
Tell your users. Disclose that recipe content and imagery are AI-generated, in a way that's clear at the point they see it.
Don't present it as medical or clinical guidance. Our nutrition data is not a diagnostic tool and must not be marketed as one.
Verify allergens independently before relying on them in any consumer-facing product.

These duties are also set out in the API License Agreement and the Terms of Service.

Safety Notice

AI-generated recipes can be wrong. Language models can produce inaccurate, incomplete or fabricated content, including incorrect quantities, unsafe combinations, wrong cooking temperatures and missed allergens.

Foodashi is not medical, clinical, or nutritional advice. Do not use this data to make decisions about the treatment or management of any medical condition, and do not present it to your users as capable of doing so.

Allergen data must be independently verified. If your application serves people with allergies, our allergen indicators are a starting signal, never a guarantee.

We run automated quality gates over every recipe before publication — ingredient resolution, nutrition ceilings, authenticity checks against known dish definitions — and we reject recipes that fail them. That reduces the error rate. It does not eliminate it, and we will not claim it does.

Models & Regulatory Position

Recipe text and classification are generated using Google's Gemini model family. Recipe imagery is generated using the FLUX model family via DeepInfra. We may change model providers as the field moves; this page will be updated when we do.

Risk classification. Under the EU AI Act, we assess Foodashi as a limited-risk AI system subject to the transparency obligations of Article 50. It is not a prohibited practice under Article 5, and it does not fall within the high-risk categories of Annex III. We do not offer Foodashi as a medical device, a diagnostic tool, or a clinical decision-support system, and the API License Agreement forbids using it as one.

No training on your data. We do not use your API queries or your application's data to train models.

Questions, or think we've got something wrong? Email [email protected]. If you're evaluating Foodashi for a regulated context and need something specific documented, ask — we would rather have that conversation before you build than after.