One engine. Many applications.
Real GDP per capita growth · 2014–2024
71.4%
Canada’s GDP per capita as a share of the U.S. — down from 83.1% in 2014. Growth of 0.4% a year: third-lowest among 38 advanced economies, and below the OECD average for the first time on record.
Source · The Hub (2026), OECD
Small teams, larger output.
Automate routine. Keep judgement.
Applied intelligence is the lever.
The engine builds once; every application deploys it.
Owned signal & distribution
Applied AI for lean teams
Privacy-preserving research
Video-native signal
Live data at the edge
Low cost to launch
One research team improves every application at once. That is the moat.
Shared engineering, data and compliance. New applications launch at low marginal cost.
Research compounds; infrastructure is already paid for.
Real-time, video-native behavioural AI
Most of the world's information is video. Crystal AI reads it.
AI agents that handle repetitive workflows so lean teams can operate at scale without adding headcount.
Models that read attention, sentiment, and intent from video-native signal to predict what happens next.
Live surfaces that turn fragmented data into reachable audiences at the edge of every platform.
Proprietary distribution and signal networks built for exclusive, high-signal access others cannot buy.
Early directions, not a roadmap.
01Threat detection for security operations
02Multimodal understanding of live environments
03Behavioural signal in high-stakes decision making
04Agentic systems for regulated industriesThree active hubs. A fourth on the way.
DIFC HQ · regulated
Research lab
Research lab
Coming soon
Built ventures at the intersection of media and technology for 17 years, including co-founding Daily Hive and scaling it into one of Canada's largest digital publishers. He now leads Brilliant as an applied research lab, setting the direction for how one engine turns into many applications and pushing the case that capability, not headcount, is what closes the country's productivity gap.
Systems and security engineer with a background at Apple Security, where he worked on the hard end of trust, privacy, and scale. At Brilliant he architects the research engine underneath every product surface — agentic automation, behavioural modelling, and the private network intelligence that keeps sensitive work inside its own perimeter.
Get brief notes on what the lab ships next.
