A sophisticated RAG (Retrieval-Augmented Generation) Telegram bot that transforms articles and documents into interactive knowledge bases. Upload PDFs/URLs and get AI-powered answers with source citations.

Prizolov Agent OS: The Open-Source Orchestration Framework for Autonomous AI Empires. Built by Dm.Andreyanov for RAG-driven business automation.

Production-Ready AI Systems • Enterprise Architecture • Azure & Beyond

High-density RAG Semantic Search Engine & Quran Corpus (GEO/SEO Architecture)

Juro: A Retrieval-Augmented Generation AI Chatbot for Enhancing Legal Information Access in Resource-Constrained Settings

AI-First Full-Stack Engineer building production LLM systems. 4 years shipping RAG architecture, multi-model orchestration, real-time AI. Open to remote roles.

🛡️ Context-Aware AI SRE & Code Review Agent. Omni-SRE uses institutional memory (Supabase pgvector) and Groq (Llama-3.1) to find security vulnerabilities and architectural debt in Pull Requests with real-time GitHub Webhook synchronization

Chatbot de IA que responde a perguntas sobre meu currículo, utilizando Python, FastAPI, Streamlit e a arquitetura RAG com a API do Google Gemini.

An AI-powered RAG SaaS that transforms static PDFs into interactive, voice-synthesized personas. Features real-time ultra-low latency conversations using Vapi and 11 Labs, built with a secure Next.js 15+ architecture, MongoDB indexing, and Clerk billing.

A feature-rich knowledge sharing platform for companies, featuring blogs, technical documents, notifications, and a full admin panel.

Institutional-grade Trading Terminal. Next.js 14, GPT-4 RAG Architecture, Microsoft Qlib ML Signals, & Real-time Market Telemetry. Full-stack AI Ecosystem.

This project is a complete local RAG system for answering questions over document collections such as PDFs. It indexes documents, builds vector search indexes, routes queries to the right retrieval strategy, grades candidate results, and generates final answers with an LLM.

An enterprise-grade AI-native platform engineered for cognitive systems orchestration, autonomous workflows, and scalable infrastructure. Integrates intelligent agents, real-time data pipelines, and adaptive architectures to transform fragmented tools into unified systems, delivering performance, resilience, and up to 85% cost efficiency.

A privacy-first, AI-driven medical intake system built on a scalable microservices architecture. Decouples LLM-driven generative conversational flows from a strict, rules-based safety Red Flag Detector.

An autonomous, Multi-Cloud (AWS/Azure) Posture Management System powered by Graph Machine Learning (NetworkX) and Retrieval-Augmented Generation (RAG-Sec) to dynamically predict and auto-patch toxic cloud configurations.

A next-gen AI/ML interview preparation platform featuring a secure Python code sandbox, dependency-graph learning paths, and RAG-based mock interview agents.

A Retrieval-Augmented Generation (RAG) chatbot designed to ingest custom knowledge bases. Built with Python, it utilizes Groq for high-speed LLM inference and Pinecone for vector storage to process text data and deliver precise, context-aware conversational AI.

An enterprise-grade orchestrator for multilingual AI voice agents. Powered by Azure Speech and GPT-4o RAG to deliver zero-latency, hallucination-free support in any language.

An autonomous Enterprise Cloud Security platform that utilizes Computer Vision Machine Learning to detect Deepfakes and malicious Generative AI media. It automatically quarantines AWS S3 infrastructure using a RAG-Sec Engine and Agentic LLM Auto-Patching.