Content Compliance Verification Using LLM Validation Logic

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Solution Overview

Problem

Existing compliance checking processes for content items, such as texts, images, and videos, are inefficient, labor-intensive, and prone to inaccuracies due to the limitations of deterministic logic and the potential for Large Language Models (LLMs) to hallucinate, making them unsuitable for large-scale and accurate compliance checks.

Innovation Solution

A system utilizing tailored prompts and validation techniques to guide LLMs in generating compliance results, incorporating preprocessing and post-processing to ensure accuracy, and employing multiple LLMs for parallel processing to enhance efficiency and reduce hallucinations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual compliance checking processes are used, then accuracy may be maintained through human judgment, but productivity is severely limited and turnaround time is extended to days or weeks

Engineering Contradiction:

Improvecompliance check throughputVSAvoidturnaround time

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The patent replaces manual mechanical review processes with an automated system combining LLMs and deterministic logic engines. The LLM extracts compliance claims from content, the deterministic engine verifies them against rules, and the system automates the entire workflow from content ingestion to compliance certification, eliminating human labor bottlenecks while maintaining accuracy

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent introduces an intermediary deterministic logic engine that acts as a mediator between the LLM's natural language processing capabilities and the rigid compliance rules. This intermediary translates LLM-generated claims into verifiable logical statements, enabling automated verification without sacrificing the flexibility of AI-based content understanding

Inventive Principle:

Principle #24Intermediary (Mediator)

2Productivity

If LLMs are used for compliance checking, then productivity and speed are improved, but reliability deteriorates due to hallucinations and inaccuracies

Engineering Contradiction:

Improvecompliance check efficiencyVSAvoidcompliance check accuracy

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The patent implements a feedback mechanism where the deterministic logic engine validates LLM-generated compliance claims against the actual content and rules. When discrepancies are detected (hallucinations or inaccuracies), the system flags them for review or automatically corrects them, creating a closed-loop feedback system that continuously improves reliability while maintaining high productivity

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The patent performs preliminary extraction of compliance claims by the LLM before verification by the deterministic engine. This preliminary action allows the system to quickly identify potential compliance issues that can then be systematically verified, maintaining speed while preparing accurate data for the reliability-checking phase

Inventive Principle:

Principle #10Preliminary action

3Reliability

If deterministic logic is used for compliance checking, then reliability is maintained through rule-based verification, but adaptability decreases when handling complex or ambiguous content

Engineering Contradiction:

Improvecompliance verification accuracyVSAvoidhandling of complex content

Core Design Contradiction:

ReliabilityVSAdaptability or versatility

Solution Approach 1:

The patent segments the compliance checking process into distinct phases: LLM-based claim extraction, deterministic verification, and exception handling. This segmentation allows each component to specialize - the LLM handles adaptability in understanding complex content, while the deterministic engine ensures reliability in rule verification, combining both strengths in a unified system

Inventive Principle:

Principle #1Segmentation

4Productivity

If multiple LLMs are deployed for parallel processing, then productivity increases through concurrent analysis, but device complexity increases

Engineering Contradiction:

Improveparallel processing capacityVSAvoidsystem architecture complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent designs the deterministic logic engine as a universal verification component that can validate compliance claims from any LLM against any set of rules. This multi-functional design allows the same verification infrastructure to support multiple LLMs and various compliance frameworks, increasing productivity through parallel processing without proportionally increasing complexity

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS20250238811A1Automated compliance verification of regulated content items in a content page

Publication Date: 2025.07.24 COMPLYAUTO IP LLC

AI summary

Computer-implemented systems and methods are disclosed, including systems and methods for performing compliance testing using language models or other machine learning models. A computer-implemented method may include, for example, accessing a content item; accessing a compliance ruleset; executing a compliance checker that utilizes a set of machine learning models; generating a prompt that includes the content item and the compliance ruleset; processing the prompt using the compliance checker; responsive to receiving a compliance determination dataset that indicates whether the content item satisfies one or more criteria within the compliance ruleset from the compliance checker; and generating an output based at least in part on the compliance determination dataset.