CASE STUDY
AI for critical infrastructure
Structuring and managing a computer vision solution on critical infrastructure, connecting product development, technology and operations.
Context
Cyclope.ai / Vinci Autoroutes
Automated detection and monitoring in a road operations environment with demanding requirements for robustness, field coordination and adoption by operational teams.
Challenge
What needed to be secured
Turn AI’s technological potential into an operational, governed and sustainable service in a constrained environment.
Role
My contribution
Technical and functional lead for the roadmap, connecting product, technology, operations and deployment, with responsibility for cross-functional coordination and sound decisions.
- Aligned product, technology, operations and field stakeholders
- Structured data flows, monitoring and critical dependencies
- Prepared acceptance testing, production deployment and adoption
- Supported operational stabilisation and improved reliability
Impact
Outcome and environment
The solution gained robustness, operational clarity and the ability to be deployed progressively in a demanding industrial environment.
Environment