Problems We Can Help You Solve
As AI decision-makers, you might be facing critical challenges, such as:
Ensuring that AI-generated outputs consistently comply with regulations and internal standards.
Mitigating the risk of logical inconsistencies or inaccuracies in automated reasoning.
Validating complex, domain-specific AI-generated content efficiently and reliably.
Enhancing transparency and explainability of critical AI-driven decisions.
Building robust confidence in AI systems handling safety-critical or high-stakes tasks.
Formal Foundry addresses these issues head-on, using practical, verifiable approaches grounded in formal verification and proof assistants.
How We Help
Formal Foundry specializes in applying proof assistants—tools originally designed to verify mathematical proofs and software correctness—to enhance the reliability of AI systems.
What is a Formal Proof?
A formal proof is a detailed logical argument checked step-by-step by a computer. Unlike informal reasoning in natural language (which can be ambiguous), formal proofs must be precisely defined, leaving no room for misunderstandings or hidden errors.
What is a Proof Assistant?
A proof assistant is software that helps humans construct formal proofs and rigorously checks their correctness. A critical component is the typechecker, which automatically verifies that each step in the logical argument is valid and consistent.
What Does Formalization Mean?
Formalization means translating informal or intuitive statements (such as business rules, regulations, or domain knowledge) into a precise, logical language understandable by proof assistants. This initial process requires careful human expertise, as it involves clearly defining and encoding domain-specific knowledge without ambiguity.
However, once formalized, the encoded knowledge can be automatically and repeatedly checked by proof assistants—without further human involvement. This allows you to quickly verify that your system consistently meets the defined standards, providing clear, automated proofs of correctness or compliance whenever needed.
What’s Practically Achievable—and What’s Challenging?
Achievable:
Clearly defined rules, logical conditions, and domain-specific workflows can typically be formalized effectively. Examples include validating compliance, consistency of generated documents, or correctness in structured decision-making.Challenging:
Formalizing highly abstract or ambiguous concepts (like nuanced human judgment or vague subjective criteria) is often difficult or impractical. Additionally, formalization requires domain expertise and careful human guidance.
At Formal Foundry, we combine deep human expertise in proof assistants (including Agda, Coq, and Lean) with automation from LLMs, delivering practical, testable solutions for robust and trustworthy AI.