A Manifesto for
Human Intelligence.
EdTech software is stuck in static video lists and flat text feeds. AskMe AI was created to design a **Cognitive Operating System** that dynamically adapts to how your neural networks retrieve information.
We leverage high-dimensional vector embeddings, custom mathematical calibration indices, and socratic chat interfaces to accelerate cognitive speeds and reduce memory decay.
Our Mission
To maximize human cognitive efficiency and reduce studying stress. We believe studying shouldn't feel like a chore; it should feel like an integrated sync between your brain and a high-performance system.
Our Cognitive Philosophy
Every component in AskMe AI is grounded in clinical neuroscientific research.
Active Retrieval Over Passive Reading
Re-reading notes creates an illusion of competence. We force active extraction and recall through adaptive question generation.
Memory Decay Compensation
Syllabi are calculated using mathematical exponential decay models. Reviews are triggered right before you are forecasted to forget.
Meta-Cognitive Tracking
We don't just score tests. We map calibration—monitoring if you are overconfident, underconfident, or correctly balanced.
Timeline Milestones
Our journey towards cognitive intelligence models.
Research & System Design
Designed the RAG pipeline architecture. Selected Supabase pgvector as vector store and prototyped Gemini text-embedding-004 chunking experiments.
Core Engine Build
Built the document ingestion pipeline, quiz generation engine, memory graph data model, and Learning DNA schema. First full internal end-to-end demo.
Cognitive Learning OS Launch
Launched AskMe AI on Vercel. Full RAG chat, adaptive quizzes, 3D memory graph, Learning DNA profiling, and study planner all live.
Open Source & Community
Published on GitHub under MIT license. Accepting contributors and building the first external user community.
Built By
The mind behind the Cognitive Learning Operating System.