Muhammad Hamad J.

Most AI projects die somewhere between the demo and production. I'm the engineer clients bring in to get them shipped. I build complete AI Products designed, developed, and shipped end to end. 7+ years of experience building AI and SaaS Platforms, Full-Stack development, IoT Web and Mobile app development, RAG knowledge assistants/Chatbots and intelligent automation, 30+ delivered projects, and apps shipped to millions of users from AI mobile apps on the App Store & Play Store to full AI SaaS platforms. I work with founders and product teams worldwide to take AI products from concept to production. 𝐖𝐡𝐚𝐭 𝐈 𝐁𝐮𝐢𝐥𝐝: ➛ AI-Powered Mobile Apps (Flutter & React Native, iOS & Android) ➛ AI-Powered SaaS Platforms & Web Apps (full-stack, cloud-deployed) ➛ LLM & RAG Systems: LangChain, Pinecone, OpenAI, Claude, Llama ➛ Chatbots & AI Assistants (in-app, customer support, business automation) ➛ Voice AI & Calling Agents (Twilio, Vapi, Deepgram, Real-time Conversations) ➛ Multi-Agent Systems & Workflow Automation (n8n, Make, Zapier) ➛ End-to-End Deployment (AWS, Azure, Google Cloud, Docker, CI/CD) ➛ MVPs & Prototypes – From idea → shipped product quickly 𝐏𝐫𝐨𝐝𝐮𝐜𝐭𝐬 𝐈'𝐯𝐞 𝐒𝐡𝐢𝐩𝐩𝐞𝐝: • Clinic Cue: HIPAA-Compliant patient queue management platform for dental and medical offices. • Ekvi: Health symptom-tracking app that helps women with endometriosis log pain, mood, and menstrual data to spot patterns and prepare for consultations. • EtonVS: Intercom support automation - automates support ticket creation, routing, and multi-channel notifications inside Intercom. • Ascensus: AI journaling companion - Flutter app, OpenAI with RAG memory, voice and text. • ChatQRE: AI Chatbot - natural-language queries over databases and live market APIs, analyst-hours replaced by seconds. 𝐔𝐬𝐞 𝐂𝐚𝐬𝐞𝐬 𝐈 𝐒𝐩𝐞𝐜𝐢𝐚𝐥𝐢𝐬𝐞 𝐈𝐧: 🔑 AI-powered mobile apps with chat, voice, and real-time features 🔑 AI SaaS platforms – from MVP to production release 🔑 AI chatbots and assistants for support, sales, and onboarding 🔑 RAG-based knowledge assistants over documents and internal systems 🔑 Voice AI for call handling, summaries, and insights 🔑 Task-focused AI agents with controlled tool access (MCP-based) 🔑 Workflow automation across SaaS tools and custom platforms 🔑 Data pipelines, syncing, reporting, and operational analytics 𝐓𝐞𝐜𝐡𝐧𝐢𝐜𝐚𝐥 𝐄𝐱𝐩𝐞𝐫𝐭𝐢𝐬𝐞 𝐌𝐨𝐛𝐢𝐥𝐞 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 🔹 Cross-platform Flutter and React Native apps with AI chat, voice interfaces, and real-time features 🔹 BLE/IoT, biometric auth, real-time data, and payments integration 🔹 Cross-platform builds from MVP to App Store / Play Store production release 𝐒𝐚𝐚𝐒 & 𝐂𝐮𝐬𝐭𝐨𝐦 𝐖𝐞𝐛 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦𝐬 🔹 Custom web applications using React, Next.js, TypeScript, Redux, Tailwind CSS 🔹 Secure REST, GraphQL, and Fast API with Node.js, NestJS, Python (FastAPI, Flask, Django), WebSockets 🔹 Scalable databases: PostgreSQL, MongoDB, MySQL, DynamoDB, Firebase, Supabase, Redis 🔹 API & platform integrations: Stripe, PayPal, Plaid, Google Maps & GPS, email and social platforms 𝐂𝐡𝐚𝐭𝐛𝐨𝐭𝐬 & 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬 🔹 OpenAI, Claude, and Gemini LLM Integration 🔹 Multi-agent orchestration with LangChain, LangGraph, and custom frameworks 🔹 MCP (Model Context Protocol) server for AI-powered applications 🔹 Vector databases for semantic search and long-term memory (Pinecone, ChromaDB, Elasticsearch) 🔹 Retrieval-Augmented Generation (RAG) over existing databases, PDFs, and internal documents 🔹 Voice & calling agents using Retell, Twilio, and Vapi 🔹 Speech-to-text and text-to-speech pipelines (Whisper, Deepgram, Google Speech APIs) 𝐖𝐨𝐫𝐤𝐟𝐥𝐨𝐰 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧𝐬 🔹 CRM, lead management, and workflow automation with n8n, Make, Zapier, HubSpot 🔹 AI-powered automations for onboarding, follow-ups, scheduling, reporting, and notifications 🔹 End-to-end data pipelines for analytics, alerts, and operational intelligence 🔹 API-level integrations connecting AI agents, databases, SaaS tools, and cloud services 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 & 𝐈𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞 🔹 CI/CD pipelines with GitHub Actions, GitLab CI, and automated testing 🔹 Containerized deployments using Docker and Kubernetes orchestration 🔹 Monitoring, logging, and observability with Sentry, Datadog, CloudWatch 🔹 Scalable cloud architecture on AWS (Lambda, EC2, RDS), GCP, and Azure If you're building an AI mobile app or SaaS product and want it done once, properly, send me a short description of what you're building and I'll tell you honestly what it'll take.