Misha and Tahin met at Stripe, where they worked on high-scale risk and fraud systems — blending machine learning with distributed systems to protect billions in payments. Across roles at Stripe, Mercury, and Interac, they've spent over a decade building risk systems that turns real-world signals into actionable insight.

With deep experience across AI, engineering, and data science, they started Canonical Labs to solve a hard but common problem: how to catch fraud faster, scale ops without adding headcount, and bring clarity to messy signals. Their work helps financial institutions reduce losses, improve decision systems, and build automation.

Canonical partners with high-growth teams to tackle the problems that traditional vendors ignore — from reducing alert fatigue to unblocking approvals, accelerating market expansion, and bringing AI into production risk workflows.