Cortex: Industrial AI Knowledge Platform

Problem: Industrial organizations maintain thousands of pages of manuals, SOPs, maintenance guides, equipment specifications, engineering reports, and compliance documents. Critical knowledge is fragmented across PDFs, making retrieval slow and preventing engineers from answering questions that require combining information from multiple documents. Traditional RAG systems retrieve isolated chunks of text but fail to capture relationships between assets, procedures, failures, regulations, and components. Solution: Cortex is an Industrial Knowledge Intelligence Platform that transforms unstructured documents into a living knowledge graph and enables engineers to interact with it using a multi-agent AI system. Instead of retrieving only text, Cortex combines: Layout-aware document understanding Knowledge graph construction Dense vector retrieval Graph traversal Multi-agent reasoning to answer complex industrial questions with complete citations and provenance. Key Features Layout-aware PDF parsing Knowledge Graph generation Hybrid Retrieval (Dense + Graph) Multi-Agent AI Copilot Streaming responses Interactive graph exploration Explainable answers with citations Production-grade asynchronous ingestion JWT-secured backend Self-healing background workers AMD Compute Usage All machine learning workloads execute on AMD GPUs through AMD AI Notebooks. The unified inference gateway serves: ROCm + vLLM for LLM inference IBM Docling for PDF parsing and OCR FastEmbed for embedding generation The backend communicates with the gateway through OpenAI-compatible APIs without requiring model-specific code. Real-World Applications Manufacturing Energy Oil & Gas Chemical Plants Aerospace Industrial Compliance Asset Maintenance Technical Documentation Search