The Department of National Defence (DND) has launched a new Innovation for Defence Excellence and Security (IDEaS) challenge, seeking artificial intelligence solutions capable of fusing multi-domain data streams, including satellite imagery and telemetry, to improve real-time situational awareness for the Canadian Armed Forces (CAF).
The challenge, titled “Multi-modal AI for advanced situational decisions,” opened on April 23 and offers up to $6.75 million in phased development funding. DND is looking for architectures that move beyond traditional rule-based data aggregation. Instead, the department is seeking AI models that can ingest heterogeneous data—such as electro-optical (EO) video, radio frequency (RF) signals, sensor telemetry, and text reports—and provide explainable, policy-aware outputs to operators.
While the challenge spans all operational domains, the required capabilities are tied to Canada’s space defence efforts. The solicitation highlights “Joint ISR [Intelligence, Surveillance, and Reconnaissance] Fusion for Arctic Operations” as a primary application. For this use case, the CAF is seeking the “spatiotemporal” alignment of satellite imagery, RF signals, and telemetry to establish persistent Arctic domain awareness.
Because Canada relies heavily on space-based assets, such as the RADARSAT Constellation Mission, to monitor vast northern territories, the military generates large volumes of orbital data. These data streams currently remain siloed. The IDEaS challenge indicates that AI is required to process this data deluge at the tactical edge to prevent human operators from being overwhelmed, integrating intelligence across domains and classification levels.
The DND initiative aligns with broader trends in space domain awareness and operational resilience. As noted in recent global counterspace capability reports, the normalization of electronic warfare and signal spoofing has made space a contested operational domain. In response, the IDEaS challenge specifies a need to fuse radar, Electro-Optics/Infra-red (EO/IR), and telemetry to enhance the detection and tracking of “stealth or spoofed adversary assets.”
This AI-driven focus on data fusion complements other recent Canadian defence activities in the space sector. It follows efforts to bolster sovereign space domain awareness, such as MDA Space’s contract for Canadian space surveillance observatories, and the funding of early-stage commercial satellite architectures like NordSpace’s Kestrel VLEO constellation concept.
Funding for the challenge is structured across three phases based on Technology Readiness Levels (TRL). Lower TRL solutions (TRL 1-3) are eligible for up to $250,000 for a six-month development period. Design phase solutions (TRL 4-5) can receive up to $1.5 million over 12 months, while the build phase (TRL 6-9) offers up to $5 million to validate prototypes in varied environments.
The deadline for innovators to submit proposals is June 2, 2026.