| # SPARKNET | |
| ## AI-Powered Research Valorization Platform | |
| **A Multi-Agent System for Patent Wake-Up and Technology Transfer** | |
| --- | |
| ## What is SPARKNET? | |
| SPARKNET is an intelligent platform that analyzes patent documents and research to: | |
| - **Assess commercialization potential** | |
| - **Identify technology applications** | |
| - **Match with industry partners** | |
| - **Accelerate technology transfer** | |
| Built on modern AI agent architecture with LangGraph workflow orchestration. | |
| --- | |
| ## System Architecture | |
| ``` | |
| ┌─────────────────────────────────────────────────┐ | |
| │ SPARKNET Multi-Agent System │ | |
| ├─────────────────────────────────────────────────┤ | |
| │ │ | |
| │ ┌──────────┐ ┌──────────┐ ┌──────────┐ │ | |
| │ │ Frontend │ │ Backend │ │ LLM │ │ | |
| │ │ Next.js │◄─┤ FastAPI │◄─┤ Ollama │ │ | |
| │ │ Port 3000│ │ Port 8000│ │ 4 Models │ │ | |
| │ └──────────┘ └──────────┘ └──────────┘ │ | |
| │ │ │ | |
| │ ┌────────┴────────┐ │ | |
| │ │ LangGraph │ │ | |
| │ │ Workflow │ │ | |
| │ │ (State Machine)│ │ | |
| │ └────────┬────────┘ │ | |
| │ │ │ | |
| │ ┌────────────────┼────────────────┐ │ | |
| │ │ │ │ │ | |
| │ ┌───▼───┐ ┌────▼─────┐ ┌───▼───┐ │ | |
| │ │Planner│ │ Document│ │ Critic│ │ | |
| │ │ Agent │ │ Analysis│ │ Agent │ │ | |
| │ └───────┘ │ Agent │ └───────┘ │ | |
| │ └──────────┘ │ | |
| │ ┌───────┐ ┌──────────┐ ┌────────┐ │ | |
| │ │Memory │ │ VisionOCR│ │ Vector │ │ | |
| │ │ Agent │ │ Agent │ │ Store │ │ | |
| │ └───────┘ └──────────┘ └────────┘ │ | |
| │ │ | |
| └─────────────────────────────────────────────────┘ | |
| ``` | |
| --- | |
| ## User Workflow | |
| ### Simple 4-Step Process: | |
| 1. **Upload** → User uploads patent PDF | |
| 2. **Process** → Multi-agent system analyzes document | |
| 3. **Assess** → Technology readiness & commercial potential evaluated | |
| 4. **Results** → Interactive dashboard with insights and recommendations | |
| ``` | |
| Upload PDF → Auto-Extract → Multi-Agent Analysis → Results Dashboard | |
| │ │ │ │ | |
| │ ├─ Title ├─ TRL Assessment ├─ Patent Details | |
| │ ├─ Abstract ├─ Key Innovations ├─ Technical Domains | |
| │ └─ Claims ├─ Applications ├─ Commercialization | |
| └─ Partner Matching └─ Recommendations | |
| ``` | |
| --- | |
| ## Core Components | |
| ### 1. **Frontend (Next.js + React)** | |
| - Modern, responsive UI | |
| - Drag-and-drop file upload | |
| - Real-time workflow visualization | |
| - Interactive results dashboard | |
| ### 2. **Backend (FastAPI)** | |
| - RESTful API architecture | |
| - Async processing pipeline | |
| - CORS-enabled for frontend integration | |
| - Comprehensive logging | |
| ### 3. **LLM Layer (Ollama)** | |
| - **4 specialized models**: | |
| - `gemma2:2b` - Simple tasks | |
| - `llama3.1:8b` - Standard complexity | |
| - `qwen2.5:14b` - Complex reasoning | |
| - `mistral:latest` - Analysis tasks | |
| ### 4. **Agent System** | |
| - **PlannerAgent**: Orchestrates workflow steps | |
| - **DocumentAnalysisAgent**: Extracts patent structure & content | |
| - **CriticAgent**: Reviews and validates outputs | |
| - **MemoryAgent**: ChromaDB vector store for context | |
| - **VisionOCRAgent**: Image/diagram extraction (llava:7b) | |
| ### 5. **Workflow Engine (LangGraph)** | |
| - State machine-based execution | |
| - Parallel agent coordination | |
| - Error handling & recovery | |
| - Checkpointing for long-running tasks | |
| --- | |
| ## Key Features | |
| ✓ **Intelligent Document Analysis** | |
| - Automatic title & abstract extraction | |
| - Patent claims identification | |
| - Technical domain classification | |
| ✓ **Technology Assessment** | |
| - TRL (Technology Readiness Level) scoring | |
| - Innovation identification | |
| - Novelty assessment | |
| ✓ **Commercialization Analysis** | |
| - Market potential evaluation | |
| - Application domain suggestions | |
| - Partner matching recommendations | |
| ✓ **Multi-Format Support** | |
| - Standard patent PDFs | |
| - Press releases & technical docs | |
| - Fallback extraction for non-standard formats | |
| --- | |
| ## Technology Stack | |
| | Layer | Technology | | |
| |----------------|-------------------------------------| | |
| | Frontend | Next.js 16, React, TypeScript | | |
| | Backend | FastAPI, Python 3.10 | | |
| | LLM Framework | LangChain, LangGraph | | |
| | AI Models | Ollama (local deployment) | | |
| | Vector Store | ChromaDB | | |
| | Vision | llava:7b (OCR & diagram analysis) | | |
| | Development | Hot reload, async/await | | |
| --- | |
| ## Current Status | |
| ### ✅ Operational | |
| - Multi-agent system fully initialized | |
| - All 4 LLM models loaded | |
| - Workflow engine running | |
| - Frontend & backend connected | |
| ### 📊 Capabilities Demonstrated | |
| - Patent PDF processing | |
| - Document extraction (with fallback) | |
| - TRL assessment | |
| - Technical domain classification | |
| - Commercialization potential scoring | |
| --- | |
| ## Use Cases | |
| ### 1. **Patent Wake-Up (Primary)** | |
| University tech transfer offices can: | |
| - Rapidly assess dormant patent portfolios | |
| - Identify commercialization opportunities | |
| - Match technologies with industry needs | |
| ### 2. **Technology Transfer** | |
| - Evaluate research outputs | |
| - Prioritize licensing opportunities | |
| - Generate technology briefs | |
| ### 3. **Partner Matching** (Future) | |
| - Connect inventors with industry | |
| - Identify potential licensees | |
| - Facilitate collaboration | |
| --- | |
| ## Sample Analysis Output | |
| ```yaml | |
| Patent: Toyota Hydrogen Fuel Cell Initiative | |
| ───────────────────────────────────────────── | |
| Title: "Toyota Opens the Door to Hydrogen Future" | |
| Abstract: "Toyota announces royalty-free access to 5,680 fuel | |
| cell patents to spur hydrogen vehicle development..." | |
| Technical Domains: | |
| • Automotive Technology | |
| • Clean Energy Systems | |
| • Fuel Cell Engineering | |
| TRL Level: 8 (System Complete & Qualified) | |
| Commercialization Potential: HIGH | |
| Key Innovations: | |
| • High-pressure hydrogen storage | |
| • Fuel cell stack optimization | |
| • System control software | |
| Applications: | |
| • Hydrogen vehicles | |
| • Stationary power systems | |
| • Industrial fuel cells | |
| ``` | |
| --- | |
| ## Why SPARKNET? | |
| ### **Problem**: | |
| - Manual patent analysis is slow and expensive | |
| - Technology transfer offices overwhelmed | |
| - Valuable IP sits dormant in university portfolios | |
| ### **Solution**: | |
| - **Automated**: AI agents handle complex analysis | |
| - **Fast**: Minutes instead of days | |
| - **Scalable**: Batch processing capability | |
| - **Intelligent**: Multi-model approach ensures accuracy | |
| --- | |
| ## Next Steps | |
| ### Immediate (v1.0) | |
| - [ ] Enhance patent structure extraction | |
| - [ ] Add batch processing for multiple patents | |
| - [ ] Improve TRL assessment accuracy | |
| ### Short-term (v1.5) | |
| - [ ] Industry partner database integration | |
| - [ ] Automated technology brief generation | |
| - [ ] Export to PDF reports | |
| ### Future (v2.0) | |
| - [ ] Real-time collaboration features | |
| - [ ] Market trend analysis integration | |
| - [ ] Automated prior art search | |
| --- | |
| ## Demo Access | |
| - **Frontend**: http://localhost:3000 | |
| - **Backend API**: http://localhost:8000 | |
| - **API Docs**: http://localhost:8000/docs | |
| - **Health Check**: http://localhost:8000/api/health | |
| --- | |
| ## Team & Contact | |
| **Project**: SPARKNET - Research Valorization Platform | |
| **Architecture**: Multi-Agent AI System | |
| **Framework**: LangGraph + LangChain | |
| **Deployment**: Local (Ollama) / Cloud-ready | |
| **For more information**: See documentation in `/home/mhamdan/SPARKNET/` | |
| --- | |
| ## Summary | |
| SPARKNET is a **production-ready AI platform** that automates patent analysis and technology assessment using: | |
| - **Multi-agent architecture** for complex reasoning | |
| - **State-of-the-art LLMs** for accurate analysis | |
| - **Modern web stack** for seamless user experience | |
| - **Flexible deployment** options (local or cloud) | |
| **Result**: Accelerated technology transfer from lab to market. | |
| --- | |
| **Questions?** | |
| *This is a preliminary overview for initial searching and evaluation.* | |