Not metrics. Not models. Real coaching insight instantly. Any hitter. Any angle. Anywhere.
The problem is not data. It is interpretation. Most players never receive high-level diagnosis, and the advice they do get is often generic and not tailored to the hitter.
Not what happened, but why it happened. We identify cause and effect relationships, surface patterns unique to each hitter, and deliver decisions instantly.
No hardware. No special cameras. Any coach with a smartphone can access a layer of understanding that used to require years of elite coaching experience.
From raw swing video to root cause diagnosis and drill prescription, in under 60 seconds.
Every hitter needs feedback. Very few get great feedback. The $8B+ market growing at 22% per year (Compound Annual Growth Rate) barely touches the 35M amateur players who need it most. We unlock elite coaching at scale.
Every competitor gives athletes numbers. We are the only platform that delivers coaching decisions, what it means, why it happened, and exactly what to do next.
Built, deployed, and generating early revenue, with inbound interest from multiple MLB organizations before we have even initiated enterprise sales.
A direct-to-athlete subscription generates recurring revenue at scale while institutional licensing captures high-value, sticky enterprise contracts.
We start where trust lives with athletes on the field, then we follow the conversation upward as results prove value at every level.
The industry is solving the wrong problem. Every competitor measures movement, compares hitters to ideal models, and outputs numbers instead of decisions. They analyze swings. They don't diagnose hitters. That is the gap we fill.
Building a product like this requires someone who speaks the language of the dugout and the data center. Dakota Sill is one of the rare few.
Conservative growth driven by athlete subscriptions as the base, with institutional licensing as the high-multiple accelerant.
The product is built. The market is validated. MLB is paying attention. We are raising to scale distribution, not to prove the concept.