This is also what we discovered at @engimeets. One of the biggest challenges we’ve seen in the Kenyan market, especially among medium-sized enterprises, is the data problem. The data exists, but it’s often scattered across systems, spreadsheets, documents, and workflows. It’s unstructured, difficult to connect, and ultimately hard to use for meaningful operations or decision-making. So we decided to tackle the problem at its foundation: the data layer. At Engimeets, we’re building infrastructure that helps organizations consolidate fragmented data into a unified, reliable layer they can actually use. Because this problem looks different across industries, our approach is to build vertical-specific data infrastructure, per tenant. Our first flagship product is Atlas, built specifically for freight forwarders. We went live with our first Atlas engagement this week, an implementation estimated to run for about five months. Over that period, our goal is to build a robust ontology for freight forwarding and establish reliable data pipelines that transform the client’s scattered operational data into a unified layer they can use for day-to-day operations, analytics, and decision-making. In simple terms: Engimeets builds the data layer. Atlas applies it to freight forwarding. And freight is just the beginning. We’re building toward a world where businesses don’t have to fight their own data before they can use it. engimeets.com

Yes, that’s true. One of my learnings too. In logistics, for example, I am yet to encounter any regulation restricting our development and implementation of a TMS The only one with complex compliance is fintech. Others, you have an environment where you can build, test and iterate. If you’re looking at expanding into US/European markets like what we are doingat @engimeets, you can compromise on the check at the moment as you build a more resilient and robust product.