Team Data Clustering API for Custom Team Service Delivery

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Solution Overview

Problem

Large organizations face challenges in effectively organizing and utilizing large volumes of team data to derive value due to the sheer volume and complexity of the data, making it difficult to customize tools and services for different teams.

Innovation Solution

A system and method for clustering team data using machine learning techniques, storing the clusters via an API, and providing cluster information as a service to generate customized tools and services for different team clusters.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Quantity of substance

If traditional data organization methods are used for large volumes of team data, then data storage is achieved, but data organization efficiency and utilization effectiveness deteriorate

Engineering Contradiction:

Improvevolume of team dataVSAvoiddata organization efficiency

Core Design Contradiction:

Quantity of substanceVSProductivity

Solution Approach 1:

The patent replaces traditional mechanical data organization methods with machine learning-based automated clustering algorithms. The system automatically processes and groups team data using computational intelligence, eliminating manual intervention and significantly improving data organization efficiency while handling large volumes of team data across multiple variables.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Loss of information

If team data is collected across multiple variables for comprehensive analysis, then data completeness improves, but data complexity and processing difficulty increase

Engineering Contradiction:

Improvecompleteness of team dataVSAvoidcomplexity of data processing

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The patent introduces machine learning algorithms as intermediaries between raw multi-variable team data and actionable insights. These algorithms automatically process complex data relationships, perform feature extraction, and generate meaningful clusters, thereby managing data complexity while preserving information completeness across multiple team variables.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Adaptability or versatility

If customized tools and services are created for each individual team, then service customization improves, but resource requirements and system complexity increase

Engineering Contradiction:

Improvecustomization of team toolsVSAvoidcomplexity of service delivery system

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent merges teams with similar characteristics into clusters, allowing customized tools and services to be designed at the cluster level rather than for each individual team. This approach maintains service customization and adaptability while significantly reducing system complexity and resource requirements by serving multiple teams through unified cluster-based solutions.

Inventive Principle:

Principle #5Merging (Combining)

Data Source

PatentUS20260056977A1Team data clustering as a service

Publication Date: 2026.02.26 STATE FARM MUTAL AUTOMOBILE INSURANCE COMPANY

AI summary

Techniques described herein relate to clustering team data and providing the resulting cluster information as a service. The cluster information provided as a service can be efficiently incorporated into tools and services of utility for the teams from which the team data is gathered.