Ali Hussain, founder of New York-based AI fintech startup Tabs, built the company from a non-traditional background rooted in humanities and operations rather than computer science. Hussain’s early years in his family’s St. Paul convenience store instilled a strong work ethic, while his academic path—including a Cornell degree in comparative politics and a Marshall Scholarship to Oxford—diverged from conventional tech trajectories.
After abandoning a Ph.D. program at 23, Hussain transitioned to management consulting at Boston Consulting Group before taking a significant pay cut to join Latch, a seed-stage startup, as its first operations hire in 2015. Over six years, he helped scale Latch to tens of millions in revenue, gaining firsthand experience in venture-backed growth, team-building, and problem-solving in large markets.
In 2023, Hussain applied those lessons to launch Tabs, an AI platform automating revenue recognition, billing, and collections. Recognizing his own technical limitations, he partnered with co-founder Deepak Bapat, a technical expert, to balance the company’s commercial vision with deep-tech execution. The strategy resonated with investors, who backed Tabs with a $4 million pre-seed round led by Primary Venture Partners and One Way Ventures.
Since then, Tabs has expanded to roughly 180 employees and raised approximately $92 million in total funding, achieving a $400 million valuation in its most recent round. The company has reported triple- to quadruple-digit year-over-year revenue growth, positioning it among the emerging AI-driven fintech firms reshaping enterprise finance workflows.
Hussain attributes the startup’s progress to leveraging non-traditional backgrounds as a strategic advantage, emphasizing resilience and adaptability in navigating early-stage uncertainty. "Sometimes it’s just the non-traditional background that allows you to embrace non-traditional ways of learning that ultimately get you into entrepreneurship," he said in a recent interview.
Tabs’ rapid ascent reflects broader trends in AI adoption across finance, where automation tools are increasingly targeting operational bottlenecks in billing, compliance, and financial reporting.
