The story behind Brake Point

A father tries to teach his 6-year-old son to ride. Year after year, the traditional coaching approach fails.

"Brake later", "Look ahead", "Feel the bike" — the subjective, intuition-based advice that works for most riders doesn't reach him.

His son is autistic. Human bias, feelings, the unspoken intuition of an experienced rider — none of it translates. His mind doesn't process the world through vague human signals. He processes through structure, patterns, data.

The father — also a software engineer — understands: the problem isn't his son. The problem is that riding knowledge is locked behind a wall of complex data matrices that only experienced race engineers can read.

The telemetry data exists. The answers are in the numbers. But who translates them?

A professional race engineer costs thousands. Data analysis tools show raw traces that mean nothing to a beginner. The gap between "the data exists" and "I understand what to do" is enormous.

2026: BudAI. An AI race engineer that reads the data, understands the patterns, and explains — clearly, objectively, without human bias — what the numbers mean.

"You brake 12 meters too early at turn 3. Move your braking point past the 100m board."

Not intuition. Not "feel". Data. Structured. Actionable. Accessible.

For his son. For every rider who deserves a race engineer in their pocket.

"Make telemetry accessible to every rider — not just those who can afford a race engineer."