SECURING AI CORRECTNESS AT SCALE

We are practitioners bringing formally verified reasoning to AI applications

We help teams formalize their domain knowledge and automate the reasoning behind it. Using proof assistants, we prevent hallucinations, codify complex rules, and deliver verifiable, trustworthy outcomes — especially where correctness and compliance truly matter.

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Formal Foundy AI
Safe AI
OUR OBJECTIVE

Correctness at Scale

Safe AI Through Rigorous Methods

We provide the foundation of verifiable safety to AI systems. AI has advanced quickly, but most operational safeguards still rely on heuristics—prompts, pattern checks, red‑teaming, and test suites. These controls are useful yet inherently brittle: behaviour drifts, wording is interpreted inconsistently, and corner cases accumulate. For homeland security and safety work, this variability is hard to accept. The durable alternative is formal verification: expressing requirements as precise specifications that can be checked by a proof assistant. In practice, the barrier has been formalisation—turning expert intent and knowledge into exact, machine‑checkable definitions. It is slow, specialist, and difficult to audit. Formal Foundry addresses this bottleneck. 

Explore the Architecture

We are entering an era where the ability to ensure Correctness At Scale will be critical for AI operators, one that will integrate formal methods, machine learning, and software development.

– Marcin Grzybowski, Founder

Our technology may be complex, but our explanations aren't.

Whether you’re a novice or an expert, we break down our approach in a way that makes sense for you. No matter your role or expertise, we’ve got you covered with an explanation of our technology that fits your level of experience. 

Explanation for everyone

Listen (3:54) or Read

You will learn:

  1. The distinction between heuristics and provably correct solutions in AI.
  2. How our startup merges AI with proof assistants for reliable, efficient outcomes.
  3. The future potential of AI and proof assistant collaborations in various domains.

Explanation for developers

Listen (7:05) or Read

You will learn:

  1. The role of type systems in language safety and the balance between safety and flexibility.
  2. The potential of dependently typed languages for enhancing AI safety and their challenges.
  3. How AI advancements can transform proof assistants and contribute to safer AI systems.

Explanation for experts

Listen (3:42) or Read

You will learn:

  1. How we efficiently progress by leveraging existing tools without reinventing the wheel.
  2. Our approach for integrating proof assistants with AI.
  3. How our demonstrations cohesively fit together, potentially forming a functioning system with further refinement.