Sabi AI
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Next-Gen Explainable Adaptive Learning Engine

Learning Should Adapt to You.
Master Anything in Real-Time.

Traditional LMS platforms force everyone down the exact same 4-hour video playlist. Sabi uses Generative AI to architect custom Directed Acyclic Graphs (DAGs), mathematically routed by Operations Research (OR) and FSRS memory decay.

Generate First CurriculumExplore Learning Hub
sabi-core-engine • live-vector-routing
FSRS-Lite Active
✓

Module 1: Variables & Memory Scope

Prerequisite mathematically satisfied (100%)

Completed
Current Focus • OR Optimal StepEst. 15 mins

Module 2: Asynchronous Event Loops

Decayed retention dropped to 68%. Socratic AI intervention scheduled before proceeding to advanced Promises.

68% Retention
Launch Session →

Why traditional EdTech fails you.

We abandoned flat playlists and static multiple-choice quizzes to build an explainable learning engine that treats education as a mathematical supply chain routing problem.

1. Respects Your Time Budget

If you only have 15 minutes, Sabi's OR engine calculates the mathematically optimal, highest-yield concept you can internalize in that exact window without overwhelming cognitive load.

2. Decoupled FSRS Memory

We cleanly separate static module completion badges from dynamic retention. Your personalized forgetting curve mathematically schedules review sessions right before memory fades.

3. Socratic AI Tutoring

Multiple-choice quizzes promote guessing over understanding. Sabi acts as a strict Socratic evaluator, forcing you to explain concepts in your own words before granting mastery.

Under The Hood

Explore Sabi's Cognitive Math

decision.ts • Edge Graph Algorithm

Multi-Dimensional Node Scoring

Sabi evaluates four concurrent variables to pick your next study module: Prerequisite Eligibility (raw mastery >= 0.70), Spaced Repetition Priority (intercepting decayed nodes), Time Fitting (matching your available minutes), and Goal Relevance.

  • Deterministic acyclic dependency traversal
  • Automatic review interception when retention < 0.70
  • Zero-latency edge computation without UI blocking
// OR Routing Scoring Math
const score = (gapWeight * 0.4) + (timeFit * 0.3) + (urgency * 0.3);
if (node.currentMastery < REVIEW_THRESHOLD) {
return prioritizeReviewNode(node); // Intercept graph!
}
100%

Deterministic Routing

0.60

Proficiency Threshold

< 1s

JIT Graph Generation

0

Static Video Playlists

Ready to experience the future of learning?

Initialize your personalized cognitive model today. Start learning any topic with AI-guided mastery.

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