Safe, Verifiable AI Code Generation for Mission-Critical Systems

Verifiable AI isn’t about faster code; it’s about trustworthy innovation. Europe is leading the way by proving that safety and speed can coexist.

Artificial Intelligence is revolutionizing enterprise software development and deployment. Yet, in regulated and safety-critical sectors—finance, healthcare, and public services, the priority is no longer speed, but trust. Unverified AI-generated code can hide vulnerabilities and compliance risks that organizations cannot afford.

According to Gartner (2024), 62% of European companies cite “security and compliance” as the main barrier to adopting AI in development. Most code generated by current Large Language Models still contains exploitable flaws.

“For industry leaders, the question is no longer if AI will accelerate innovation, but how to adopt it responsibly.”¹

The Research Breakthrough: From Faster Code to Verifiable Intelligence

At HES-SO Valais-Wallis, Professor Andrei Kucharavy, Alexander Sternfeld (Research Associate), and their team at the Reliable Information Lab are pushing the boundaries of AI-assisted development. They integrate Large Language Models (LLMs) with formal verification techniques in Scala, using frameworks like Stainless from EPFL.

Their method extends beyond code generation to include automatic correctness proofs. Each Scala function created by an AI is systematically verified against formal specifications using tools like Stainless or TypePilot, which not only ensure compilation but also mathematically verify the function’s behavior. When a function successfully passes verification, it is not only functional but also guaranteed to be safe, compliant, and resilient, requiring no human intervention. This approach represents more than an improvement; it signifies a fundamental shift, transforming AI from mere productivity enhancement to a robust base for scalable, verifiable innovation.

For now research are still ongoing to improve formal verification : teams are working on reinforcement learning to resolve it. For now, team is using Scala type system and compiler to ensure safety through agentic type refinement, meaning that if the code compiles, it is safe. You can only pull it off with three programming languages, Scala, Rust and Swift, that have a sufficiently strong type system and sufficient adoption for LLMs to be able to generate their code well.

Real-World Impact

This work has immediate implications across industries:

• In finance, logic errors in transaction processing can be eliminated before reaching production.
• In healthcare, control software for medical devices can guarantee safety and regulatory compliance by design.
• In public infrastructure, systems managing utilities or transportation gain reliability where downtime can’t be tolerated.

Early results show that Scala’s type system and verification ecosystem outperform similar approaches in other languages, offering a distinctively European route to safe and accountable AI.

“Europe doesn’t need more AI code. It needs verifiable AI.”¹

The Business Advantage of Verifiable AI

Beyond mere compliance, verifiable AI reshapes the economics of software development. It reduces the need for extensive manual code audits, helping enterprises save costs and enabling expert teams to focus on innovation. Verified code significantly minimizes vulnerabilities, making cybersecurity an integral aspect rather than an afterthought. Additionally, since verified systems naturally conform to ISO, GDPR, and industry standards, compliance becomes seamless; an inherent feature rather than an ongoing audit challenge. Speed and trust are no longer at odds; they coexist effortlessly compound.

Building Safe, Verifiable AI Together

Safe and verifiable AI code generation requires a foundation as strong as the innovation itself. Gartner predicts that by 2027, over 75% of regulated sector enterprises will need formal verification or similar safeguards for AI-generated code. At the same time, IDC estimates that more than 60% of European companies will move sensitive workloads back from non-EU clouds to ensure compliance and sovereignty.

This intersection shapes Exoscale’s mission. Exoscale provides a European sovereign cloud built to support AI at scale, where performance, legal assurance and European governance naturally coexist.

Exoscale brings the transparency and dependability often missing from global providers: consistent performance, clear pricing, and human support. Whether using GPU instances or integrated Kubernetes and DBaaS services, enterprises can develop and verify safely through every phase, from proof of concept to production, with SLA-grade guarantees.

“Innovation thrives when performance is built on trust.”¹

Strategic Value

AI in software development is now essential rather than optional. However, for leaders in regulated industries, trust will be the key differentiator. With Exoscale’s sovereign cloud and the innovative efforts of HES-SO, Europe demonstrates that responsible AI can be both rapid and verifiable. Companies no longer need to choose between innovation and compliance; they can achieve both confidently and with control. The future belongs to those who innovate with speed, safety, and sovereignty in balance. Your next breakthrough can be quicker, more secure, and sovereign; the foundation is already in place.

If you’d like to explore the technical side of this collaboration, from Scala’s verification frameworks to implementation pipelines, read our next article by François Mouraine, “Scala and Verifiable AI: From Concept to Code”, and/or watch Professor Kucharavy’s full session on YouTube.