About FRAME
Across the European research landscape, modern software engineering and data practices must ensure absolute reliability, safeguard privacy, and maintain transparency.
While the EU and international standard bodies have established foundational guidelines for trustworthy AI, a massive gap remains. Research institutions and software developers face immense practical challenges when trying to translate these abstract principles into real-world code.
Fragmented Standards
Developers rely on custom, fragile setups to secure autonomous systems.
Rapid Tech Growth
It is difficult to adapt safety rules to complex, emerging tools like AI agents and collaborative robots without slowing down innovation.
FRAME bridges the gap between academic safety theory and real-world launch. Funded by the EU’s Horizon Europe program, our 3-year project is building an open-source software foundry. This acts as a digital guardrail, enforcing strict validation and privacy before an AI agent can execute a command.
Project Objectives
Foundation
Architectural Modeling
Building formal design blueprints and execution contracts so that multi-agent AI systems behave predictably and reliably.
Standardise
Middleware Connectivity
Creating open-source, standardised connectors so engineers can safely link, swap, and isolate digital tools and micro-services.
Secure
Continuous Auditing
Integrating automated validation engines that continuously stress-test running AI networks against security threats and error loops.
Safeguard
Uncertainty Containment
Developing “uncertainty alarms” that instantly halt an AI pipeline if data is missing or corrupted, safely passing control back to a human.
Validate
Real-World Launch
Testing the complete software foundry inside high-stakes environments across our three focus industries: automation, healthcare data tracking, and industrial robotics.