As a dedicated full-stack developer with a BS in Computer Science, I specialize in crafting reliable, AI-powered applications and automation systems. My expertise lies in building scalable solutions using modern technologies, ensuring seamless integration of AI for enhanced efficiency and innovation. I deliver trustworthy results that meet client needs precisely, positioning myself as the ideal partner for advanced AI-driven projects.
Building intelligent agents and automation systems
- Education — Bachelor of Science in Computer Science
- Experience — Hands-on development of production-grade AI systems using Python, JavaScript/TypeScript, React, Express, gRPC, Docker, and modern AI/ML stacks
- Specialization — Agentic AI • RAG pipelines • NLP applications • TTS systems • Voice Cloning • Intelligent automation • Full-stack AI platforms
- Mission — To deliver clean, scalable, and dependable AI-powered solutions that give clients a real competitive advantage
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| Project Name | Repository Link | Description |
|---|---|---|
| Echo — Memorial Voice AI | View Repo | Deeply personal AI application that clones the voice of a loved one using local XTTS v2 (Coqui) — no cloud APIs required. Upload voice recordings, then text or speak naturally and receive responses in their cloned voice. Powered by Groq Whisper (STT), Llama 3.3 70B (LLM), LanceDB RAG pipeline for semantic memory, and sentence-transformers for local embeddings. Full-stack FastAPI + Vanilla JS frontend. |
| Story-Audio-TTS Microservice | View Repo | Production-grade microservice that transforms story prompts into emotionally rich audio narratives. Uses Falcon-RW-1B for intelligent text enhancement and Kokoro-82M for high-quality TTS. Includes gRPC API, async processing, smooth audio stitching with crossfades, Docker deployment, and Gradio frontend. |
| Qatar Labor Laws Chatbot | View Repo | Accurate, RAG-powered legal assistant delivering grounded answers on Qatar labor regulations. Built with n8n automated data pipelines into Supabase vector store, Cohere embeddings, and Groq LLM inference. Features secure responses, context-aware handling, and intuitive Gradio interface. |
| GBR – AI Consultation Platform | View Repo | Full-stack intelligent matching system connecting clients with domain experts. Supports secure registration, detailed consultation requests, and AI-driven expert allocation based on requirements. Clean React frontend with reliable backend logic and smooth user flows. |
| LLM Explorer 2026 | View Repo | Modern full-stack web application for exploring 60+ LLMs. Includes ranked leaderboard, fuzzy search, semantic model matching, and RAG-powered chatbot. Powered by React + Tailwind frontend, Express backend, Supabase pgvector, Cohere embeddings, and Groq inference. |
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Let's build something powerful together.
Open to collaborations on agentic AI, RAG systems, voice AI, automation, and intelligent full-stack applications.