Runtime Enforcement Templates for Scalable Partner Condition Validation

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Customizing software code to manage and validate computer-detected events based on specific conditions is time-consuming, labor-intensive, and error-prone, leading to scalability and throughput issues.

Innovation Solution

A system extracts conditions from natural language documents using machine learning models, generates machine-readable data structures, and applies these structures to validate events in real-time, reducing the need for customized code and storage space.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Manufacturing precision

If software code is customized to manage and validate computer-detected events based on specific conditions, then the validation accuracy and specificity to conditions is improved, but the development time and labor intensity increase

Engineering Contradiction:

Improvevalidation accuracyVSAvoiddevelopment time

Core Design Contradiction:

Manufacturing precisionVSLoss of time

Solution Approach 1:

The patent uses templates to capture conditions and generates machine-readable data structures as copies that can be reused across multiple events and partners. Instead of customizing code for each condition set, the system creates reusable template instances that maintain validation accuracy while eliminating repetitive development work.

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The system performs preliminary actions by pre-defining condition templates and their corresponding machine-readable data structures before actual event validation occurs. This advance preparation allows rapid deployment of validation logic without time-consuming customization during event processing.

Inventive Principle:

Principle #10Preliminary action

2Manufacturing precision

Engineering Contradiction:

Improvevalidation accuracyVSAvoiderror rate

Core Design Contradiction:

Manufacturing precisionVSReliability

Solution Approach 1:

By using templates to generate consistent machine-readable data structures, the system eliminates manual coding errors while maintaining validation accuracy. The template-based copying ensures that the same validation logic is applied consistently across different events and partners, reducing variability and error rates.

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The system automatically generates machine-readable data structures from templates without requiring manual code customization. This self-service approach reduces human error in code writing and maintenance while preserving the ability to accurately validate events against specific conditions.

Inventive Principle:

Principle #25Self-service

3Adaptability or versatility

If customized software code is used to implement condition validation, then the adaptability to specific partner conditions is improved, but the scalability and throughput decrease

Engineering Contradiction:

Improveadaptability to conditionsVSAvoidthroughput

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

The patent creates universal templates that can serve multiple partners and event types simultaneously. A single template can be instantiated multiple times with different parameters to validate various conditions across different business relationships, eliminating the need for separate customized code for each partner while maintaining full adaptability to specific conditions.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system uses template instantiation to create multiple copies of validation logic that can be deployed across numerous events and partners. This copying mechanism enables scalable deployment where the same validated template structure handles high volumes of events without requiring additional customization for each case.

Inventive Principle:

Principle #26Copying

4Extent of automation

If machine learning models are used to extract conditions from natural language documents, then the automation level and reduction of manual work is improved, but the complexity of the system increases

Engineering Contradiction:

Improveautomation levelVSAvoidsystem complexity

Core Design Contradiction:

Extent of automationVSDevice complexity

Solution Approach 1:

The patent introduces templates as an intermediary layer between natural language conditions and machine-readable data structures. The machine learning model extracts conditions from natural language and maps them to predefined template structures, which then generate the final machine-readable output. This intermediary simplifies the overall system by providing a structured intermediate representation that bridges unstructured input and structured output.

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS20260064965A1Partner management runtime enforcement

Publication Date: 2026.03.05 CITIGROUP

AI summary

A set of conditions extracted from a natural language document is obtained. Context information applicable to the set of conditions is obtained. A computer-readable data structure is generated based at least in part on the set of conditions and the context information, the computer-readable data structure being usable to determine, based at least in part, on context associated with an operation subject to the set of conditions, whether the operation is fulfillable.