🧠 Intelligent Textbooks for AI-Native LMS
- Company: TBD
- Subtitle: Redefining Learning with Graphs, Vectors, and AI
- Presenter: Dan McCreary, Founder
🚨 The Problem
- Traditional LMS platforms are built on outdated relational databases
- Minimal personalization, static content, weak recommendations
- Students need adaptive, intelligent, and engaging learning tools
🌍 The Opportunity
- $200B+ global EdTech market by 2027
- Demand for hyper-personalized, AI-powered education
- GenAI enables smart content and adaptive learning paths
🎯 Our Vision
Build an AI-native LMS with intelligent textbooks that adapt to every learner using knowledge graphs, LLMs, and vector embeddings
🛠️ Our Product: GraphLearn.ai
- Graph-based Learning Management System
- AI-generated interactive MicroSims
- Personalized learning paths via concept graphs
- Embedded LLMs for Q\&A, feedback, and tutoring
⚙️ Innovation Comparison
| Feature | Traditional LMS | GraphLearn.ai |
|---|---|---|
| Database | Relational | Native Graph DB |
| Content | Static | AI-generated MicroSims |
| Personalization | Limited | Concept Graph Traversal |
| Search | Keyword-based | Semantic via Vectors + LLM |
🧱 Tech Stack
- Graph DB: TigerGraph / Neo4j
- Vector Store: FAISS / LanceDB
- LLM Integration: LangChain, Ollama
- Modular plug-in architecture
🔁 How It Works
- Knowledge Graph models concepts and dependencies
- MicroSims linked to concepts
- Learner progress tracked and routed
- LLM + vector search for tutoring and support
🧪 AI-Generated MicroSims
- Visual, hands-on simulations
- Automatically generated from concept graphs
- STEM-focused (e.g., circuits, chemistry, algebra)
- Interactive, adaptive, and context-aware
🧭 Personalized Learning Paths
- Algorithmic routing through concept graphs
- Paths adjusted based on mastery
- Explains prerequisites and recommends review
- "Why am I learning this?"—Answerable via graph context
🖥️ Demo Screens (Mockups)
- LMS dashboard
- Concept graph visualization
- Example MicroSim: Ohm’s Law, balancing equations, etc.
💸 Business Model
- B2B SaaS: Subscription for schools and training programs
- B2C Freemium: Direct to learners and parents
- Custom LMS integrations: White-label licensing
🚀 Go-to-Market
- Pilot with charter and STEM-focused schools
- Target early adopters in EdTech innovation
- Showcase AI-powered content creation advantages
- Emphasize cost savings via automated lesson gen
🏁 Competitive Landscape
| Platform | Graph DB | Vectors | LLMs | Personalization |
|---|---|---|---|---|
| Canvas | ❌ | ❌ | ❌ | Limited |
| Moodle | ❌ | ❌ | ❌ | Limited |
| Khan Academy | ❌ | ❌ | Some | Moderate |
| GraphLearn.ai | ✅ | ✅ | ✅ | Full AI-native |
📈 Traction & Early Results
- 2 pilot schools
- 1,200+ MicroSims created
- 40% faster concept mastery
- Strong interest from 3 LMS vendors
🌐 Market Size
- EdTech: $200B by 2027
- AI in Ed: $25B+
- TAM: $2B in STEM-focused institutions
👥 Team
- Dan McCreary: Founder, AI + Graph DB expert
- CTO (TBD): EdTech platform architect
- Advisors: Curriculum experts, AI ethicists, GTM strategists
📊 Financial Projections
| Year | Revenue | Schools | Users |
|---|---|---|---|
| Y1 | $500K | 5 | 5,000 |
| Y2 | $2M | 25 | 50,000 |
| Y3 | $8M | 100 | 250,000 |
💰 Funding Ask
- $2M Seed Round
-
Use of Funds:
-
40% Product Development
- 30% Sales & GTM
- 20% Content/AI tuning
- 10% Legal/Admin
🎓 Let’s Build the Future of Learning
“The future of learning isn’t linear—it’s a graph.”
LinkedIn: https://www.linkedin.com/in/danmccreary/