CTX: a tool that solves the context management gap when working with LLMs like ChatGPT or Claude. It helps developers organize and automatically collect information from their codebase into structured documents that can be easily shared with AI assistants.

Personal AI project manager with Claude Code integration and persistent context

🧠 LLMs don’t just process text — they read the room. Meaning emerges through context — shaped by tone, trust & trajectory. Most benchmarks flatten that. This one maps it.

Project Agora: MVP of the Concordia framework. An ethical, symbiotic AI designed to foster and protect human flourishing.

Advanced multi-agent Medical AI Assistant powered by LangGraph that delivers empathetic, doctor-like responses using a hybrid pipeline of LLM reasoning, RAG from medical PDFs, and intelligent fallback tools. Features Long-term memory with SQLite, dynamic tool routing, and state reasoning for reliable, context-aware consultation.

The Customer Support Ticket Classification and Response System combines advance AI models with RAG to automate and elevate ticket categorisation and response generation. By leveraging multi-model integration, sentiment analysis, urgency detection, and vector-based retrieval, it delivers precise, context-aware responses and actionable insights.

🤖 NoCapGenAI is a Retrieval-Augmented Generation (RAG) chatbot built with Streamlit, Ollama, MongoDB, and ChromaDB. It features a clean, modern UI and persistent vector memory for context-aware conversations. Easily integrates with Ollama-supported models like phi3:mini, llama3, mistral, and more. Designed to support customizable assistant modes

A decentralized protocol for agent trust, dialogue, and influence in open multi-agent systems.

An intelligent, context-aware Q&A backend powered by Groq LLM and Django REST Framework. Supports real-time chat, multi-turn memory, and blazing-fast responses. Seamlessly integrates with a React frontend available in a separate repo.

A privacy-first browser extension that detects text inputs on any webpage, and generates context-aware replies using selectable LLMs.

A stateful AI agent framework powered by the Cognitive Lattice to solve complex tasks with persistent memory and reliable tool orchestration.

Context-aware tool for automated BDD test generation and execution using RAG, VectorDB, and LLaMA.

Artificial-intuition–driven pattern recognition system under high noise & scarce data environments. Validated on real-world datasets with proven generalization, robustness & scalability.