MenuClaw transforms billions of unstructured restaurant menus into structured, AI-readable data — powering the next generation of AI assistants, search engines, POS systems, and food platforms.
MenuClaw turns fragmented restaurant menus into structured, connected data that AI products and software platforms can query through APIs.
It normalizes menus from PDFs, images and websites into restaurants, dishes, ingredients, nutrition and prices. Teams use the data for food assistants, search, ordering, analytics and model training instead of maintaining their own menu extraction pipeline.
The world's food data is the most fragmented data on the internet. AI is ready to help people eat — but it has nothing structured to read.
A single restaurant's menu is scattered across PDFs, photos, websites, delivery apps and POS systems — each in a different format, language and schema.
Menus are crafted for eyeballs and appetites — not machines. Dishes hide their ingredients, portions are implicit, nutrition is invisible. AI models starve on this.
AI assistants, search engines, ordering platforms and analytics all need the same thing: clean, connected, queryable data about restaurants, dishes, ingredients and prices.
One infrastructure layer that turns the fragmented world of food into a queryable, connected, AI-ready system of record.
AI agents extract clean, structured menu data from websites, PDFs, images, and delivery platforms — at global scale, in any language.
Learn moreA global semantic graph connecting restaurants, dishes, ingredients, cuisines, allergens and attributes — millions of entities, one queryable web.
Explore graphDeveloper-first REST APIs built for AI applications. Query dishes, menus, ingredients and nutrition with one predictable interface.
Read the docsEnterprise-grade datasets purpose-built for training and fine-tuning food-aware AI models — clean, licensed, continuously refreshed.
Explore datasetsA living semantic web where Tokyo Ramen Shop connects to Tonkotsu Ramen, connects to pork bone broth, connects to Japanese cuisine. Hover to explore.
"Spicy pork ramen" and "Tonkotsu Ramen Spicy" resolve to the same dish across 40 languages and every menu format.
Dishes know their ingredients. Cuisines know their dishes. Allergens propagate. Prices track by location and time.
Every day the graph ingests millions of menu changes so your applications never serve stale food data.
One predictable REST API. Query any restaurant, dish, ingredient or nutritional fact in the graph with a single call.
// Restaurant Intelligence API { "restaurant": "Tokyo Ramen", "cuisine": "Japanese", "dishes": [ { "name": "Tonkotsu Ramen", "ingredients": ["pork", "egg", "noodles"], "calories": 720, "allergens": ["egg", "gluten"] } ] }
Every layer of the food industry is becoming intelligent. MenuClaw is the data foundation they build on.
Every restaurant we index makes the graph smarter. Every smart API makes our customers stronger. Every customer brings more data. The loop compounds.
The industry built intelligence for locations, transactions and operations. Nobody built intelligence for food itself. We did.
| Platform | Intelligence | Dishes & ingredients | AI-ready data |
|---|---|---|---|
| Google MapsLocation | Location intelligence | Limited | — |
| Delivery PlatformsTransactions | Transaction intelligence | Per-platform | Partial |
| POS SystemsOperations | Operational intelligence | Closed | — |
| MenuClawFood | Restaurant intelligence | Global graph | Native |
Short answers for teams evaluating restaurant data infrastructure.
Join the AI companies, platforms and developers building on the world's restaurant intelligence layer. Free tier. Production SLA. Enterprise support.
