About Us

Why We Started T51

We founded T51 after years of deploying planning solutions across the Fortune 500 (e.g. plane routing, production scheduling, material demand planning). We saw a persistent gap between companies' aspirations for optimization and manual decisions on the ground. What surprised us was how many tools claim to solve this—from afar, you'd think these problems are figured out. But look closely, and they almost never are.

Why? Enterprise systems force companies into rigid templates. Point solutions break down when they need to work together. Complex internal builds become unmaintainable. The result: operations teams make critical decisions using spreadsheets and intuition, leaving enormous value on the table.

An AI Paradigm Shift

For decades, software was expensive and difficult to build. So businesses settled for generic tools—systems designed to serve everyone, perfectly tailored to no one. That tradeoff made sense. Custom software meant multi-year projects and millions in development costs.

AI is changing that calculus. The barrier to building software has dropped dramatically—which means far more companies should be able to get software that actually fits how they operate. But there's a trap. AI excels at translating business rules into code and navigating well-defined domains. It struggles with architectural design, system reliability, and the judgment that comes from years of building operational systems. Teams that try to build fully custom with AI alone often end up with something that works in demos but fails in production.

Our Approach

Our platform handles the architectural foundation that operational workflows share—the patterns that take years to get right. AI handles the customization: translating your specific rules and constraints into working software. That combination lets us focus on what actually matters: working with your team, learning how decisions are really made, and getting the details right.

The result: software that models your operations as they actually work, deployed in weeks—with improvements that show up in throughput, uptime, and margins.