ScribePal is an Open Source intelligent browser extension that leverages AI to empower your web experience by providing contextual insights, efficient content summarization, and seamless interaction while you browse.

Echo is a privacy-first, offline AI journal and conversational assistant. Capture your thoughts via text or voice, analyze patterns, and chat with your entries — all without your data ever leaving your device.

Advanced RAG Pipelines and Evaluation

🚀 Productive AI: Your Customizable AI Chat Assistant

Oryx — Integrate your application with Contextual AI agents seamlessly, from interface to proxy, fully customizable and unbranded.

Making finance self explanatory with a simplified approach

A lightweight Python library providing comprehensive contextual information (time, weather, location, news, system) for AI applications with optimized prompts and graceful fallbacks

Multi-dimensional evaluation of AI responses using semantic alignment, conversational flow, and engagement metrics.

Intelligent browser extension using AI to dynamically manage tasks based on your web context. Real-time prioritization and seamless workflow integration to optimize focus and boost productivity. Supports Chrome, Firefox, and Edge.

Repository for testing and demonstrating the capabilities of Docling for document conversion.

🤖 AI-powered interview coaching chatbot built with Python, Streamlit, Claude 3.5, and Cohere embeddings — remembers chat history and delivers smart, context-aware career advice.

RTGX is an AI-powered real-time glossary explainer that adds contextual subtitles during live lectures. It transcribes speech, identifies complex terms, and provides instant, context-aware definitions using LLM, built for accessibility and multi-language support.

This protocol defines a constructive framework that synchronizes contextual understanding across text, image, and sound. It enables layered abstraction and dynamic adaptation, supporting advanced multimodal AI reasoning. 本プロトコルは、テキスト・画像・音声間の文脈理解を構成的に同期させる枠組みを定義し、階層的抽象化と動的適応により高度なマルチモーダルAI推論を可能にします。