With the incredible early success of SERV Reasoning, I’ve been focused on accelerating adoption across two key domains: Bigger institutions. Global scale. This week, I’m in Nairobi meeting with some of the largest banks in the region, including pitching heads of corporate credit, IT, and risk (among others) inside executive boardrooms at Tier 1 institutions with over $7B in collective AUM. East Africa and Kenya in particular is the highest growing credit market in the world. As banks increasingly look to adopt AI, especially in emerging markets where credit is growing rapidly, the opportunity is obvious: major bottlenecks and archaic processes are waiting to be solved. But for financial institutions, adoption only happens if the technology clears a high bar: auditable outputs, reliable performance, and sustainable cost. So far, we’ve heard that previous attempts at AI integration have largely stalled because they failed on reliability, cost, or both. That’s where SERV Reasoning comes in. To power products that actually move the needle, and that institutions can rely on to deliver results at an economically feasible price. But product is only one side of adoption. In enterprise, especially with major institutions in emerging markets, distribution can matter just as much, if not more. Sales cycles are long, trust is earned through relationships, and adoption often depends on being in the right rooms with the right stakeholders. That’s why being here on the ground matters.
