Research and Development

 Formal methods are mathematically rigorous techniques used for the development and verification of high-reliability systems.

Recently, the integration of Artificial Intelligence (AI) and Formal Methods has opened new frontiers, ranging from Automated Theorem Proving to the verification of large-scale engineering systems.

Applying formal methods throughout the development cycle ensures maximum system validity, while AI accelerates the test generation process.

Thanks to our experience we managed to successfully experiment with the combined use of Formal Methods and Artificial Intelligence to develop customised MCP servers and tools that allow fine-tuned AI models to interact directly with existing systems.

Formal methods are mathematically rigorous techniques used for the development and verification of high-reliability systems.

Recently, the integration of Artificial Intelligence (AI) and Formal Methods has opened new frontiers, ranging from Automated Theorem Proving to the verification of large-scale engineering
systems.

Applying formal methods throughout the development cycle ensures maximum system validity, while AI accelerates the test generation process.

In the verification phase, AI creates tests based on formal requirements, utilizing Retrieval-Augmented Generation (RAG) to cross-reference technical documentation. By leveraging the Model Context Protocol (MCP) architecture, our AI agents interact directly with formal verification
tools, such as SAT solvers (for the Boolean Satisfiability Problem) and detect edge cases that may escape manual analysis.

In the development phase, specialised AI models propose implementations that comply with formal specifications by design, significantly reduce correction-verification cycles and
automatically adapt code to changing requirements while preserving correctness.