Artificial Intelligence Verification for Large Language Model Protocol Adherence

Brief Description

A pioneering framework that enables formal verification of Large Language Model (LLM) compliance with specified interaction protocols using natural language and Finite State Machine (FSM) structures. It is complemented by methods for rapid protocol development and scalable multi-agent coordination.

Full Description

This technology introduces a novel method to verify whether AI language models adhere to interaction rules. It is a comprehensive end-to-end framework that checks AI behavior against protocols written in natural language and structured using Finite State Machines (FSMs). The invention has three complementary components:

• Core verification framework: Calibrates specification detail to match model capabilities, quantitatively measures protocol adherence, and supports certified deployment in safety-critical settings such as healthcare, finance, autonomous systems, and enterprise automation.
• Rapid development module: A streamlined method for designing and iterating on protocols through efficient simulation. It enables faster protocol development than traditional approaches.
• Multi-agent coordination module: Extends verification to systems of multiple cooperating AI agents, providing both per-agent and compositional guarantees. 

Together, these tools combine formal verification rigor with practical usability. They cover the full lifecycle, from protocol design through multi-agent deployment and certification. Each component can also be licensed independently to meet different user needs.

Suggested uses

Certification and compliance (core verification framework)

• Healthcare AI requiring verified clinical and safety procedures. 
• Financial services with strict regulatory and compliance requirements. 
• Autonomous systems needing guaranteed interaction protocols. 
• Regulated industries requiring auditable AI behavior. 

AI development tooling (rapid development module) 

• AI development platforms focused on testing, certification, and deployment. 
• Teams building LLM-based products that need faster, more reliable protocol design. 

Agentic systems (multi-agent coordination module) 

• Enterprise automation using coordinated multi-agent AI workflows. 
• Multi-agent AI ecosystems requiring scalable, cost-efficient verification.

Advantages

Core verification framework

• Verifies AI procedural compliance using natural language specifications. 
• Accessible to domain experts without specialized formal methods training. 
• Provides quantitative conformance metrics for certification and audits. 
• Adapts specification rigor to different AI model capabilities.
• Detects protocol violations even when outputs appear superficially correct. 
• Simplifies debugging by identifying exact failure points in AI workflows. 

Rapid development module

• Enables faster protocol development through efficient simulation. 
• Replaces trial-and-error prompt engineering with structured, verifiable iteration. 
• Reduces development cost and complexity compared to traditional approaches. 

Multi-agent coordination module

• Supports scalable multi-agent systems with per-agent and compositional guarantees. 
• Lowers the cost and complexity of testing coordinated AI agents. 

Patent Status

Patent Pending