Open-source semantic layer and knowledge engineering framework for building explainable, auditable, and trustworthy AI systems. Contributes to context graph infrastructure, semantic retrieval pipelines, and knowledge engineering tooling used across AI stacks.

⚡ Highlights

• Context graphs with causal links and decision intelligence
• GraphRAG pipelines with full W3C PROV-O provenance
• Reasoning engines: forward chaining, Rete, SPARQL, deductive
• MCP server with 12 tools for Claude, Cursor, VS Code integration
• Semantic deduplication, entity resolution, and conflict detection
• Knowledge Explorer UI — React 19 + Sigma.js live graph canvas

Tech Stack:
Python Knowledge Graphs GraphRAG Neo4j SPARQL FastAPI MCP

🔗 Repository  |  🌐 Website

Built an event-driven streaming enforcement platform using Kafka-based ingestion pipelines, Spark stream processing, Redis-backed rate limiting, and Medallion architecture for scalable analytics and validation workflows.

⚡ Highlights

• Real-time event ingestion and validation pipelines
• Distributed stream processing with Kafka and Spark
• Redis-backed rate limiting and enforcement logic
• Delta Lake + Medallion structured data layers
• Analytics and observability workflow design

Tech Stack:
Kafka Spark Delta Lake Redis Python

🔗 Repository

Built an AI-powered voice assistant integrating speech recognition, NLP reasoning pipelines, and conversational AI interaction systems with modular, extensible architecture.

⚡ Highlights

• End-to-end voice-to-text pipeline using Whisper transcription
• Multi-step NLP reasoning and response orchestration
• AI-driven conversational context and flow management
• Modular assistant architecture for extensibility
• Speech processing and AI system integration

Tech Stack:
Python Whisper NLP AI Pipelines Speech Processing

🔗 Repository

Designed a distributed analytics platform using Lambda architecture, ETL workflows, OLAP processing, and scalable backend services for city-scale data and analytical workloads.

⚡ Highlights

• Lambda architecture for batch and real-time data paths
• ETL pipeline design with structured data ingestion
• Spring Boot backend APIs for service integration
• PostgreSQL-based OLAP analytics workflows
• Event-driven backend data integration

Tech Stack:
Java Spring Boot Kafka PostgreSQL

🔗 Repository

• Knowledge Graph Engineering
• GraphRAG & Semantic Retrieval
• Context Graph Architecture
• Reasoning Engines & NLP Pipelines
• AI Provenance & Explainability
• MCP Tooling & AI Infrastructure

• REST API Design & Architecture
• Distributed Event-Driven Systems
• Authentication & Session Management
• Scalable Backend Service Design
• Real-Time System Workflows
• Backend-Oriented Full-Stack Systems

• Kafka Streaming Pipelines
• Spark Stream Processing
• ETL & Batch Workflow Design
• Delta Lake & Medallion Architecture
• Lambda Architecture Systems
• Graph Database Backends