A modern multimodal knowledge graph with type-specific metadata across biomedical domains.
An explainable AI system that combines Graph Intelligence, Vector Search, and Retrieval-Augmented Generation (RAG) to deliver grounded answers and transparent reasoning paths. Includes a FastAPI backend, Streamlit UI, FAISS vector index, and an in-memory knowledge graph for hybrid retrieval and recommendations.
Graph harness for AI agents: a governed runtime on bipartite graphs (places and transitions) that executes models with scoped permissions, durable state and replayable history.
CUDA 13 graph AI examples using cuGraph, PyTorch Geometric, GraphSAGE, transaction graphs, and reproducible CPU/GPU workflows.
Explore AI writing systems with agents, graphs, adapters, RAG, and multi-model generation workflow.
AI-powered biomedical evidence intelligence platform that transforms PubMed literature into structured claims, knowledge graphs, research briefs, and evidence-grounded AI insights.
Graph AI platform connecting equipment, processes, materials, and failure modes — enabling complex relationship queries and causal analysis across manufacturing operations
Graph-powered fraud investigation agent using TigerGraph, LangGraph, GraphRAG, Gemini, and FastAPI for policy-aware transaction analysis.
Knowledge Graph & Reasoning Engine that analyzes Python Typing PEPs to surface historical precedents, design debates, and grounded recommendations for new language proposals.
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