Group Food Order Matching Using Item Tokenization

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Solution Overview

Problem

Conventional ordering systems lack infrastructure for asynchronous, multi-user coordination, fail to tokenize items, and do not support dynamic matching based on compatibility vectors, leading to inefficiencies in group ordering and fulfillment.

Innovation Solution

A system that tokenizes item offerings, normalizes item records into a schema-aligned data model, evaluates multi-user compatibility, and generates distributed fulfillment instructions based on matched groupings, incorporating merchant-defined constraints and user preferences.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If conventional ordering systems are used, then system simplicity is maintained, but multi-user coordination capability is lost

Engineering Contradiction:

Improvemulti-user coordination capabilityVSAvoidsystem architecture complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system segments the ordering process into independent user sessions, each with their own item selections and compatibility vectors. Users can participate asynchronously without requiring real-time coordination, as each user's selections are independently processed and matched against compatibility criteria. This segmentation enables multi-user capability while maintaining relative system simplicity through independent processing units.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

A compatibility modeling layer acts as an intermediary between users and the ordering system. This layer computes compatibility vectors and matches users based on their item selections without requiring direct user-to-user coordination. The intermediary handles the complexity of multi-user matching while presenting a simplified interface to individual users.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Ease of operation

If synchronous real-time coordination is required, then coordination accuracy is improved, but user engagement and accessibility deteriorate

Engineering Contradiction:

Improveuser engagementVSAvoidcoordination accuracy

Core Design Contradiction:

Ease of operationVSReliability

Solution Approach 1:

Users make their item selections and compatibility preferences in advance during their own sessions. The system pre-computes compatibility vectors and stores them for later matching. This preliminary action allows users to engage at their own pace without waiting for real-time coordination, while the pre-computed compatibility data ensures accurate matching when users are connected.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system dynamically matches users based on their individual compatibility vectors and selections rather than requiring static real-time coordination. Users can join or leave sessions at different times, and the system adapts the matching process to accommodate asynchronous participation while maintaining coordination accuracy through dynamic compatibility evaluation.

Inventive Principle:

Principle #15Dynamics

3Manufacturing precision

If item tokenization is implemented, then fulfillment precision is improved, but data processing complexity increases

Engineering Contradiction:

Improvefulfillment precisionVSAvoiddata processing complexity

Core Design Contradiction:

Manufacturing precisionVSDevice complexity

Solution Approach 1:

The system transforms item data into tokenized representations with standardized parameters including compatibility vectors, selection counts, and fulfillment attributes. This parameter transformation enables precise fulfillment matching while the tokenization process handles data processing complexity through structured data formats and standardized processing pipelines.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS20260030590A1Systems and methods for splitting food orders between users

Publication Date: 2026.01.29 LEGACY OF 3 VENTURES LLC

AI summary

A computing system is disclosed for generating fulfillment-ready coordination sessions based on tokenized item data and user-submitted participation parameters. The system ingests structured, semi-structured, or unstructured item data from merchant sources and applies schema-aligned transformation logic to normalize the data into structured item representations. The normalized records are tokenized into machine-readable item tokens that encode fulfillment constraints and canonical attributes. The system receives user item selections and associated participation parameters, encodes the item tokens and participation data into structured vector embeddings, and applies compatibility scoring logic using vector comparison and rule-based threshold evaluation. Compatibility scores are evaluated against session eligibility constraints derived from the item tokens. When eligibility conditions are met, the system generates a coordination session payload comprising match outcomes, proportional pricing, and fulfillment metadata, and issues orchestration instructions to external fulfillment systems for group-based delivery or preparation execution.