Year 1 Prototype Priorities
Twenty-one prototypes to demonstrate NORAI capabilities and establish Canada as a global AI leader — including 6 quick-wins and 7 world-leading innovations
Priority Prototypes
Each prototype addresses a critical gap in Canada's research infrastructure
Computome: The Compute Connectome
Q1-Q2 2026 | $8M
Unified gateway and intelligent dispatcher for all Digital Research Alliance resources. Automatic routing based on queue times, data locality, and carbon footprint.
Problem:
Students wait weeks for campus clusters while national resources sit at 60% utilization. Startups pay $3/GPU-hour on AWS but cannot access Alliance resources.
Outcome:
National cluster utilization increases from 60% to 80% ($50M value/year). Startups access HPC at $1/GPU-hour. Students get same priority as professors.
Federated Data Catalog
Q1-Q3 2026 | $6M
Unified search API across all Canadian scientific repositories with FAIR metadata and OCAP compliance. Single interface to discover datasets across 13 provincial and federal systems.
Problem:
Researchers spend 40-60% of their time searching for datasets across fragmented provincial and federal systems.
Outcome:
Data discovery time reduced from weeks to minutes. 100+ datasets searchable in first release.
Consent-as-Code (OCAP Engine)
Q2-Q4 2026 | $7M
Machine-readable consent policies with blockchain-based immutable audit logs. Community-controlled dashboards for Indigenous data governance.
Problem:
No existing platform automates Indigenous data governance (OCAP) at scale. Manual compliance is slow and error-prone.
Outcome:
First platform worldwide to automate OCAP at scale. Competitive advantage over US Genesis initiative.
Provincial Data Sharing Protocol
Q2-Q4 2026 | $8M
Automated governance framework with legal compliance built-in for PIPEDA, provincial health acts, and OCAP requirements.
Problem:
Cross-provincial research requires 6+ months of legal paperwork and manual compliance checks.
Outcome:
Cross-provincial projects go from 6 months bureaucracy to 2-week digital workflow.
Critical Minerals AI
Q2-Q4 2026 | $9M
AI-powered geological analysis combining satellite imagery, geophysical surveys, and historical data to identify economically viable rare earth and lithium deposits.
Problem:
Canada needs to identify and develop critical mineral deposits to support clean energy transition and reduce dependence on foreign supply chains.
Outcome:
10 new deposit candidates identified. $15B+ potential export revenue. Support for clean energy supply chain.
PermafrostGPT
Q3 2026 - Q1 2027 | $7M
High-resolution predictive modeling for northern infrastructure resilience. Machine learning models trained on 40+ years of ground temperature data.
Problem:
Northern infrastructure faces billions in damage from permafrost degradation. Current monitoring is sparse and reactive.
Outcome:
1-km resolution forecasts. $8-12B projected savings in infrastructure protection across NWT and Yukon.
Privacy-Preserving Health Analytics
Q3 2026 - Q2 2027 | $5M
Federated learning framework enabling cross-provincial cancer research without centralizing patient data. Secure multi-party computation across provincial data enclaves.
Problem:
Provincial health data cannot be centralized due to privacy laws, blocking pan-Canadian research collaboration.
Outcome:
Analysis of 10M+ patient records with zero data centralization. 3 novel therapeutic targets identified.
Impact Projections
Data-driven projections based on current research demand, federal budget trends, and comparable investments
Canadian Federal Budget Context
NORAI investment represents approximately 12% of current federal AI and computing funding, delivering 23x returns through coordinated infrastructure and reduced duplication across agencies.