AI for Requirements Engineering in Medical Device Development
Design controls, validation, and audit readiness – solved. How Copilot4DevOps enforces traceability across requirements, risk, and validation artifacts natively inside Azure DevOps.
Aperçu
Your team already has AI. Here's what it still can't solve.
Medical device and pharma teams face a compliance reality that general-purpose AI tools weren’t built for. Design controls, validation traceability, and electronic audit trails aren’t just best practices, they’re regulatory obligations under FDA 21 CFR Part 820, ISO 13485, and FDA 21 CFR Part 11.
Missing links between requirements, risk controls, and validation evidence delay approvals, trigger audit findings, and increase compliance risk at exactly the moment it matters most. Most teams are still managing this in Word documents, spreadsheets, and disconnected tools, where changes cascade silently and nobody knows what’s broken until it’s too late.
In this session, the Modern Requirements team will show you how Copilot4DevOps enforces end-to-end traceability across your DHF artifacts, detects orphaned requirements and compliance gaps automatically, and generates audit-ready outputs – all natively inside Azure DevOps.
The compliance cost of getting it wrong
Traceability gaps aren't a documentation problem — they're a risk event
73%
of audit failures traced to broken traceability
6-18
months lost to rework when compliance gaps surface late
40%
of an engineer’s time lost to documentation and cross-referencing
Audit-ready traceability isn’t a report you generate before the audit – it’s a state you maintain every day.
Real scenarios, real fixes
What this looks like in practice
Ambiguous design inputs
“The device shall be safe and effective.”
Copilot4DevOps rewrites it: “Device shall detect adverse readings within 200ms; alert threshold defined per ISO 14971 risk analysis.”
Orphaned requirements
A design input exists with no link to a risk control, test case, or verification activity.
AI detects orphans instantly, flags them in your DHF, and suggests the right connections.
Change blind spots
“Risk classification updated” – nobody knows which specs, validations, and test protocols are now incorrect.
Blast-radius analysis maps every impacted artifact across your DHF in seconds. No manual triage.
Every one of these scenarios happens inside Azure DevOps – no new tools, no data exports, no broken handoffs.
Key takeaways
What you will leave with
01
How AI generates precise, standards-compliant design inputs from raw user needs and ISO 14971 risk inputs – automatically
02
How to maintain end-to-end DHF traceability across design inputs, risk controls, and V&V evidence without manual effort
03
A live walkthrough of Copilot4DevOps applied to a real medical device compliance scenario inside Azure DevOps
04
A replicable workflow to go from scattered documentation to audit-ready DHF outputs, in hours, not weeks
Speakers
Meet your hosts
Asif Sharif
CTO and Founder
Modern Requirements and Copilot4DevOps
Jaweria Owais
Client Success Consultant
Modern Requirements
Nevil Whitty
Senior Client Partner
Modern Requirements
Who should attend
This session is built for
- Systems engineers and software engineers on Class II and Class III medical device programmes
- Regulatory affairs and quality teams responsible for DHF completeness and audit readiness
- Programme managers under pressure to hit milestones without missing compliance checkpoints
- QA and compliance leads spending weeks on manual traceability matrices who need automation
- Azure DevOps admins and tooling leads evaluating compliant requirements tooling
- Any team currently managing design controls in Word, Excel, or disconnected tools
