The Numbers
Future Secure AI closed $115 million (US$80m) via convertible notes at a $1.7 billion valuation. Square Peg, Yarra Capital Management, and Firetrail backed the round. Third raise since launching in Sydney in 2023.
Projected ARR: US$100 million by end of 2026. ASX listing targeted for late 2027.
What They Sell
AI co-workers: supervised teams of agents that automate complex workflows in banking, consulting, healthcare, and law. The product runs inside existing enterprise systems, combining 100+ agents into persona-based teams that report to human managers.
Differentiation: not chatbots. Enterprise-grade multi-agent systems under human supervision.
The Sales Motion
Here is where it gets interesting for sales professionals: Future Secure AI does not appear to run a traditional sales org. They sell directly to CEOs and boards using consultants and engineers to scope, build, and operate bespoke AI systems.
No publicly disclosed CRO, VP Sales, or sales team headcount. Most significant hire: Todd Hewlin as president overseeing global platform and delivery.
Headcount Reality Check
Employee estimates vary wildly: 201 to 1,000 depending on the database. No verified ANZ numbers available. The company plans to triple US and Canadian headcount in the final nine months of 2026, but specifics on roles remain unclear.
Market Context
Founded by Mehrdad Baghai and Michael Hunter, who remain co-CEOs. Global HQ moved from Sydney to Austin, with offices in Melbourne, New York, Chicago, and Toronto.
The AI sales assistant market is crowded: automated sales workflows, AI prospecting tools, email management platforms. Future Secure AI plays in a different segment, targeting enterprise AI agents for complex business problems rather than sales automation tools.
What This Means
A $1.7b valuation with no traditional sales team raises questions about scalability. Consultant-led enterprise sales can work at this stage, but getting to $100m ARR typically requires structured go-to-market. Worth watching: whether they build out a sales org as they scale, or if the delivery-led model holds at scale.