Evidence-Based Alignment

The Architecture of
Aptitude Mapping.

Our system replaces generic career counseling with a dual-layer diagnostic engine: a deterministic behavioral matrix and a generative AI synthesis layer.

Layer 01: Deterministic

The 30-Point Weighted Matrix

Every user response is mapped against a high-dimensional vector space representing the **Top 20 IT Roles** in the US market. We don't just ask if you like code; we measure:

Cognitive Load Pref.
Security Risk Mindset
Architectural Logic
Data Affinity Score
// Sample Scoring Algorithm
export const calculateResult = (answers) => {
const scores = {};
answers.forEach(ans => {
ans.weights.forEach((area, val) => {
scores[area] += val * behavioralMultiplier;
});
});
return sortTopMatches(scores).slice(0, 3);
}
Layer 02: Generative

AI Synthesis Layer

Once the top roles are identified, we use **Gemini 2.5 Flash Lite** to bridge the gap between "Potential" and "Execution". The IA doesn't guess; it interprets the deterministic score to build:

Market Context

"Integrating real-time US labor demand, salary benchmarks, and local innovation hubs."

Actionable Roadmaps

"Converting technical requirements into a phased 6-month learning journey with verified resources."

Ready to test the engine?