THE AI INFRASTRUCTURE THAT SITS BETWEEN SUPPLY AND DEMAND
STRUT: The Infrastructure Layer That Exposes Mismatch Everywhere
STRUT (Semantic Targeting Reciprocal Understanding Technique) is the semantic scoring engine that measures, with ruthless precision, how well any product, service, or system reduces mismatch between what a user wants and what’s being offered. No fuzzy numbers. No marketing smoke. It delivers three individual STRUT Scores—one per idea—plus a combined total score capped at 100. Each idea maxes out at 43.3.
You don’t just see fit — you see where the mismatch lives.
Instantly. Brutally. Honestly.
This isn’t a feature.
It’s the new infrastructure layer between supply and demand.
High-Impact Use Case: Healthcare
Healthcare is a swamp of misunderstanding. Patients speak in human desires; the system responds with coded nonsense. STRUT cuts through the bullshit by exposing mismatch in plain English.
Patient enters three needs:
“I need treatment with minimal long-term side effects.”
“I want the fastest path back to full mobility.”
“I need a solution that avoids unnecessary surgical risks.”
STRUT returns three scores: one per entry plus a combined total.
Doctors see exactly where treatments match and exactly where the mismatch is too damn big to ignore.
This isn’t clinical support.
It’s clarity—weaponized.
High-Impact Use Case: Recruitment & Hiring
Hiring is a multi-billion-dollar trash fire because expectations never match reality. Resumes bullshit. Job descriptions bullshit. Companies guess. Candidates hope. STRUT exposes mismatch before the hire—not after the turnover.
Five seconds. Three scores.
Companies finally see the real gaps instead of paying to discover them later.
HR tech has been starving for this level of transparency for decades.
First Deployment: The Publishing Industry (BookStrut.com)
Book Strut is the first battlefield where STRUT’s mismatch engine is already live.
Reader enters three idea sentences:
“A woman builds a teleportation system that sends her to another galaxy.”
“She meets human-like aliens and becomes too popular.”
“She is undecided about returning to her family on Earth.”
STRUT compares each idea to the author’s declared representation.
Results might look like:
Idea 1 = 40.8
Idea 2 = 28.7
Idea 3 = 0
Total STRUT Score = 69.5
A zero? That’s a catastrophic mismatch — deal-breaker territory.
Three strong scores? Minimal mismatch. High trust.
Any genre. Any language. Fiction or nonfiction.
Book Strut is the wedge. STRUT is the underlying infrastructure.
The Economic Reality
27 industries are primed for mismatch detection at scale.
Annual TAM for key verticals:
Healthcare decision systems — $150B+
Recruiting & HR tech — $45B+
AI platforms & AI Ops — $120B+
Marketplaces & e-commerce — $300B+
Media (books, film, streaming) — $80B+
Online dating — $9–12B
Total surface: ~$707B+.
Once people can see mismatch quantified—three individual scores plus one total—they’ll never trust unscored results again.
Bottom Line
Book Strut proves the model works.
STRUT scales horizontally into almost every sector on the damn planet.
The STRUT Score becomes the new trust currency between users and the systems competing for them.
Future reality is blunt:
If it doesn’t have STRUT Scores, it won’t be trusted.
