How a 22-Year-Old Convinced Skeptical D1 Coaches to Trust His AI

While AI labs spend billions teaching robots to understand video, Mahbod Moe Sabbaghi asked a different question: Why isn't anyone building this for humans who already make high-stakes decisions on massive video libraries every day?

His company TISC (The Intelligent Search Company) just solved a problem so painful that The Globe and Mail called it "college basketball's new assistant coach."

The brutal reality: Elite coaches spend 60+ hours a week watching film, jumping between more than half a dozen different tools. Their existing tech stack? Moe's perfect description: "Search bars stapled to spreadsheets."

TISC's breakthrough: Instead of scrubbing through endless footage, coaches can ask questions in plain English:

"which offensive sets work best against Duke historically, go look at every game they've played."

The AI pulls exact clips and stats from an entire season instantly. No tagging. No grunt work. What used to take 3 hours now takes 30 seconds!

What separates TISC from every other AI sports tool is that the team embedded with coaching staffs for a year in stealth. Not building in isolation - actually sitting in film rooms understanding how game prep works day-to-day. The bottleneck wasn't lack of data; it was the hours coaches spent manually stitching it together.

The traction is undeniable:

• NCAA Division I programs using it daily for game prep

• NBA teams leveraging the platform

• US $2.1 million raised in pre-seed funding

Sports is just the wedge. They are building AI for high-stakes decision-making in the physical world. Why start with basketball? "The stakes are real but nobody dies if you get it wrong."

If you care about real AI traction, earning customer trust in skeptical markets, or building tools people use daily instead of pilot-and-forget - come to Together Toronto on March 2, hear Moe's stealth playbook, and introduce yourself after. And they are always looking for AI researchers to join the team!

NuSession: Engineering at Scale for 127M+ Customers - Feb 24 @ StartWell

Most engineering advice breaks at scale. Nubank’s was forged under it.

At NuSession Toronto, 70+ senior backend and platform engineers pressure-tested what it actually takes to run banking infrastructure for 127M+ customers, across regulatory environments, failure thresholds, and real uptime costs.

Nubank’s Renan Capaverde, Daniel Kamakura, and Vivian Isuyama, moderated by Chris Ellefson (Ollon), went deep on decisions you only face once systems are already critical.

What made the room powerful wasn’t the scale, it was watching Toronto engineers interrogate decisions that usually stay abstract until something breaks.

The panel ended. The conversations didn’t. That is the point.

Health Toronto - Feb 24 @ OneEleven

Healthcare doesn't move through consensus. It moves when constraints collide.

Health Toronto is designed to put the full system in one room - founders, clinicians, operators, investors, and policy-minded builders - because progress only happens when incentives are confronted, not avoided.

​​Anne Forsyth (Women’s College Hospital), Mary Aglipay (Pippen AI), Dr. Ivan Cacic (ProMed AI), Katie Herbert & ​Matt Zukowski (Healthkind), and Olga Cruz (BDC Capital) brought perspectives from across the stack, grounded in delivery, not theory.

This wasn't about ideas. It was about execution inside real constraints.

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