Going from an abstract vision of “AI that works for supply chain” to a functional, compliant, production-ready AI stack is harder than it sounds. At verticallm.ai, we embarked on this journey with one goal: build an AI that truly understands supply chain data, processes, and decisions—not just a generic model that spits out averages.

First, we learned that Modular design is everything. The temptation to build a monolithic system that does it all is strong—but it’s a trap. Modular design lets you integrate with existing ERP and planning systems, swap components, and scale individual pieces as your needs evolve. For supply chains, where every company’s data and processes are different, this flexibility will be very important.

Second, Observability and Transparency isn’t just a nice-to-have. When your AI is making decisions that impact inventory levels, supplier risk, or customer orders, you need to know how it got there. We invested heavily in monitoring, logging, and traceability—so that we can explain AI decisions, tune performance, and catch unexpected behaviors before they become business risks.

Third, we discovered that Low-code integration matters more than we thought. Not every company has an army of data engineers waiting to deploy a new model. A vertical AI needs to plug into existing systems with minimal friction. That means investing in connectors, API endpoints, and configuration layers that make the AI accessible to business users—not just the IT team.

Finally, scaling is a marathon, not a sprint. We had to balance fast iteration in a sandbox with governance, compliance, and performance testing before going live. Each step required hard choices: how much data to train on, how to manage regulatory requirements, how to deploy in on-premise or VPC environments for maximum security. Every decision impacted the overall resilience and reliability of the stack.

It’s been an eye-opening experience. If you’re thinking about building your own stack, or adapting AI to your industry, this post gives you a front-row seat.

Now, with our own vertical AI stack in place, we’re helping our first development partners build theirs—without the hard lessons we had to learn the hard way. We’ve gone from vision to reality, and we’re excited to help others do the same. If you’re exploring how to build or adapt AI for your industry—whether it’s supply chain, finance, or any other domain—let’s talk. We’d love to share what we’ve learned and help you build an AI stack that works for you.