dish-embed

dish-embed

A domain-specialized food embedding model built for menu intelligence at scale. Designed for food delivery platforms, cloud kitchen operators, and restaurant aggregators worldwide.

What It Does

dish-embed turns menu item text into dense vector representations optimized for food-specific tasks:

• Menu deduplication -- identify the same dish across different restaurants ("Murgh Makhani" = "Butter Chicken", but "Butter Chicken" ≠ "Butter Naan")
• Food search -- rank menu items by relevance to natural language queries, including noisy/misspelled input
• Cuisine classification -- classify items into 19 cuisine categories from embeddings alone
• Synonym retrieval -- find equivalent dish names across naming conventions and regional variants
• Cross-restaurant price comparison -- match identical items to compare pricing
• Cart recommendations -- suggest complementary items based on what's already in the cart

Benchmark Results

Evaluated at 384 dimensions against general-purpose embedding models on food-domain benchmarks.

Full interactive benchmark report: dish-embed Benchmarks

Coverage

• 20+ cuisines: Indian (North/South), Chinese, Japanese, Korean, Thai, Vietnamese, Italian, Mexican, American, Middle Eastern, Mediterranean, and more
• Multilingual support: English, Hindi, Japanese, Korean, Arabic, Spanish, Vietnamese, Thai, Chinese
• Handles real-world menu noise: pricing text, promotional tags, piece counts, abbreviations, misspellings

Access

dish-embed is available as a hosted API. No model download required.

• API: embed.statode.com
• Documentation: embed.statode.com/docs
• Contact: [email protected]

API Endpoints

Use Cases

Food delivery platforms: Deduplicate menus across partner restaurants to build a unified catalog. Power semantic search so customers find what they want even with typos or informal queries.

Cloud kitchen operators: Compare pricing for identical items across locations. Identify menu gaps and category distribution.

Restaurant aggregators: Classify menu items by cuisine for filtering and discovery. Generate menu health reports for onboarding QA.

Menu analytics: Understand what items overlap across competitors, track pricing trends for equivalent dishes, identify underserved categories.

Technical Details

• Embedding dimension: 1024 native, served at 384 (Matryoshka)
• Multilingual: 100+ languages supported at the base level, fine-tuned on food vocabulary across 9 major scripts
• Preprocessing: Built-in noise stripping and food-term normalization applied server-side
• Latency: Sub-second for single items, batch-optimized for bulk operations
• Infrastructure: Self-hosted, no data leaves the server

License

dish-embed is a commercial product. The model weights are not publicly available. Access is provided through the hosted API.

For licensing inquiries, partnership, or enterprise access, contact [email protected].