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MedTech
When compliance becomes your AI superpower: a MedTech story
In a regulated, high-stakes environment, speed and compliance can feel like opposing forces. But with Zühlke’s support, our client turned compliance into an enabler, unlocking AI-augmented delivery in medical software to accelerate delivery and improve quality, while staying fully aligned with medical standards.
Turning compliance into a catalyst for innovation
By rethinking how compliance, data and AI interact, Zühlke supported a global MedTech leader in transforming the way they deliver high-grade, regulation-compliant software.
Together, we built a development platform where AI accelerates architecture, verification and decision-making, all without compromising safety.
The project…
- Boosted alignment across architecture, requirements and verification
- Enabled AI-supported requirement checks, backlog generation and test scripting
- Strengthened compliance and quality without adding delivery overhead
The challenge: Navigating fragmented systems in a regulated landscape
Our client, a pioneering force in the MedTech industry, was on a mission to modernise how they delivered a Class C medical platform. Operating under rigorous norms – including IEC 62304, ISO 13485, and FDA regulations – they needed airtight traceability, high documentation standards and full lifecycle transparency.
But the reality was not perfect.
- Architecture lived in isolated diagrams, scattered across documents
- Requirements were distributed across siloed systems
- Documentation lagged behind development, making traceability difficult and error-prone
Our client knew AI could help, but their ecosystem wasn’t ready. They faced the core paradox of regulated AI adoption: how to safely integrate intelligent tooling into a fragmented, compliance-critical environment without introducing risk.
In short: the data was not AI-ready.
The solution: Leveraging AI to unify and accelerate development
Zühlke approached the challenge not just as a technical cleanup, but as a foundational transformation of the client’s delivery system. At the heart of our approach was the Cybernetic Delivery Method™ (CDM) – Zühlke’s structured, adaptable framework for delivering digital products and services with advanced AI assistance.
CDM is built on principles of human-centric insight, holistic systems thinking and ethical innovation. It provides teams with a stable backbone across the entire Digital Product Development Life Cycle (DPDLC), from ideation through to build and operation. In this case, CDM was instrumental in embedding consistency, traceability and the safe use of generative AI across the delivery flow.
We began by addressing the root problem: the ecosystem’s fragmentation made the data unfit for intelligent automation. The first step was to make the client’s data AI-ready, so we:
- Migrated architectural models to a structured, text-based format using Structurizr DSL.
- Centralised architectural components, relationships, decisions and references to ADRs and requirements within a version-controlled Git repository.
- Exported product and system requirements from the QMS to CSV/Markdown and indexed them using Copilot’s local vector store for efficient retrieval.
Once this step was complete, CDM enabled a repeatable, governed pathway to introduce AI responsibly and incrementally.
This structured documentation landscape became the foundation for AI-augmented delivery, enabling intelligent tooling tailored to the needs of a regulated environment. By turning architecture, requirements and design rationale into machine-readable, mineable context, we unlocked powerful capabilities that improved decision-making, reduced rework and strengthened compliance alignment.
AI now provides support in several key areas:
- Validating architectural fit before implementation: Surfacing conflicts with existing structures, layering rules or interface contracts, to ensure technical consistency and reduce rework.
- Detecting requirement contradictions early: Identifying inconsistencies across system-level and platform requirements in seconds prevents misalignment and avoids downstream defects.
- Drafting roadmaps and backlogs on demand: Generating initial epics and work breakdowns based on constraints and stakeholder input, to accelerate planning and facilitate better collaboration.
- Accelerating test script creation: Using Copilot and MCP servers to simulate device states and support verification workflows, to improve test coverage and shorten verification cycles.
- Maintaining end-to-end traceability: Mapping features, code and tests back to regulatory requirements, strengthening audit readiness and supporting compliance.
The results: Measurable improvements in delivery and quality
The transformation was immediate and measurable. What used to take days, from aligning requirements to tracking documentation or validating architecture, now happens unilaterally, in real-time.
Stakeholders across disciplines can align faster, backed by AI-generated architectural insights and tailored views.
Requirement contradictions are spotted in seconds, reducing the risk of downstream issues and boosting cross-team synergy. And developers gain instant access to architectural rationale, streamlining onboarding and ensuring that implementation matches design.
Most importantly, compliance stopped being a bottleneck and became a competitive advantage:
- Traceability is now integrated across requirements, architecture and code, allowing the team to maintain regulatory readiness without slowing down delivery
- Small quality improvements that were previously too time-consuming are now achievable – and compound over time
- Teams are empowered to innovate, knowing regulatory requirements are continuously enforced by the system
“Most people think that strict medical device regulation slows down velocity and innovation. In our case, it was quite the opposite: the discipline and structure required by standards like IEC 62304, ISO 13485, and FDA requirements became the very thing that enabled us to apply AI meaningfully.”
Setting a new standard for AI-augmented delivery in medical software
This project shows what happens when years-long experience in software engineering and software delivery in regulated environments meet the power of AI: compliance and innovation are treated as allies, not adversaries.
By transforming a fragmented legacy landscape into a connected, AI-ready system, Zühlke has helped the client harness the full potential of AI-augmented delivery in medical software.
Together, we turned a regulatory challenge into a strategic advantage – delivering better outcomes faster, and setting the stage for even more ambitious transformation.
From enabling AI-augmented verification tooling to unlocking real-time decision support, this collaboration shows how AI can become a future-proof platform for innovation, even in one of the most demanding software environments in the world.
