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Practical Software Tools for Federated Science

Open-source solutions that solve real researcher pain points while respecting Canadian sovereignty and Indigenous data governance

Federated Data
Privacy-First
Open Source
5-Line API

Platform Software Tools

Based on proven open-source technologies, adapted for Canadian sovereignty, governance, and bilingualism

Federated Data Catalog & Discovery API

Development: 3-6 months

Problem Solved:

Researchers spend 40–60% of their time searching for datasets across 13 provincial and federal systems

Solution:

Unified search API across all Canadian scientific repositories with FAIR metadata and OCAP compliance

Impact: Data discovery time reduced from weeks to minutes

Provincial Data Sharing Protocol

Development: 6-9 months

Problem Solved:

Cross-provincial research requires 6+ months of legal paperwork and manual compliance checks

Solution:

Automated governance framework with legal compliance built-in (PIPEDA, provincial health acts, OCAP)

Impact: Cross-provincial projects go from 6 months bureaucracy to 2-week digital workflow

Computome: The Compute Connectome

Development: 9-12 months

Problem Solved:

Students wait weeks for campus clusters while national resources sit at 60% utilization; startups can't afford AWS ($3/GPU-hour) but can't access Alliance resources

Solution:

Unified gateway and intelligent dispatcher for all Digital Research Alliance resources — automatic routing based on queue times, data locality, and carbon footprint

Impact: National cluster utilization increases from 60% to 80% ($50M value/year); startups access HPC at $1/GPU-hour; students get same access as professors

Federated Compute API

Development: 9-12 months

Problem Solved:

Cross-provincial research requires moving sensitive data (violating sovereignty)

Solution:

Run computation where data lives — complements Computome for federated research workflows

Impact: Enables analysis combining BC health data + Alberta climate models + NWT field data in one job without data movement

Consent-as-Code System

Development: 6-9 months

Problem Solved:

No existing platform automates Indigenous data governance (OCAP) at scale

Solution:

Machine-readable consent policies with blockchain-based immutable records and community control portals

Impact: World's first platform to automate OCAP at scale — competitive advantage vs. Genesis

Privacy-Preserving Analytics Framework

Development: 12-18 months

Problem Solved:

Cancer genomics and health research requires centralizing sensitive patient data (unacceptable for provinces)

Solution:

Federated learning + secure multi-party computation — analyze without seeing raw data

Impact: Enables research on 10M patient records with zero data centralization

NORAI SDK (Python, R, Julia)

Development: 6-9 months

Problem Solved:

Complexity barrier — researchers need simple tools, not DevOps expertise

Solution:

5 lines of code API for 80% of use cases with automatic authentication and compliance

Impact: Researchers can use NORAI immediately without training

Scientific Workflow Marketplace

Development: 3-6 months

Problem Solved:

Researchers reinvent analysis pipelines instead of reusing validated methods

Solution:

Registry of validated, reproducible workflows with one-click deployment and automatic citation

Impact: 1,200+ workflow runs saving thousands of researcher hours

Development Roadmap

Phased approach to building Canada's sovereign scientific AI infrastructure

Phase 1: MVP

Duration: 6 monthsBudget: $500KTeam: 5 developers

Key Deliverables:

  • Federated Data Catalog (search across StatsCan, NRCan, ECCC)
  • NORAI SDK (Python only) — simple API
  • Basic Compute API — submit to 2-3 clusters
  • Public Dashboard — show platform activity

Outcome: Researchers can discover and request 100 datasets, run basic jobs

Phase 2: Governance

Duration: 12 monthsBudget: $1.5MTeam: 8 developers

Key Deliverables:

  • Provincial Data Sharing Protocol — legal compliance automation
  • Consent-as-Code (OCAP automation)
  • Privacy-Preserving Analytics (federated learning)
  • Research Partnership Portal

Outcome: Cross-provincial projects with Indigenous data governance enabled

Phase 3: Scale

Duration: 24 monthsBudget: $3MTeam: 12 developers

Key Deliverables:

  • Multi-Cloud Broker — burst to Azure/AWS Canada
  • Workflow Marketplace — 100+ validated pipelines
  • SDK for R and Julia
  • Compute Credits System for equitable access

Outcome: 1,000+ active researchers, 50+ cross-provincial projects

Total Platform Software Budget
$5M
Over 3 years • All tools open-source (AGPL/MIT)

5-Year Roadmap

Strategic milestones from foundation to global leadership

2026
Foundation
  • 7 prototypes operational
  • 500+ researchers
  • Python SDK launched
2027
Expansion
  • 2,000 active researchers
  • Borealis-8B launched
  • 50+ workflows
2028
Integration
  • 5,000 researchers
  • Provincial interconnect
  • Borealis-70B
2029
Acceleration
  • 10,000 researchers
  • International partnerships
  • 17x ROI achieved
2030
Leadership
  • 15,000+ researchers
  • Borealis-671B
  • Global leader in scientific AI
$1.4B
Total Investment
15,000+
Researchers by 2030
1,000+
Jobs Created
23x
Projected ROI

Join the Mission

Help build Canada's sovereign AI infrastructure for scientific discovery. We're actively seeking partnerships with research institutions, government agencies, and industry leaders.