Usama A.

AI demo works, but breaks with real users? I build AI SaaS products, AI agents and RAG systems that hold up in production. Live with 1,000+ businesses and 5,000+ subscribers. Top Rated, with three returning clients. I own the architecture and ship the whole system: the AI layer, the product around it, and the reliability work most AI builds skip. YOU'RE A GOOD FIT IF - You're a founder with a validated idea and need a working AI MVP that won't need a rewrite once real users arrive. - You have an AI app or prototype (Lovable, Bolt, v0, Cursor, Base44 or an inherited codebase) that demos well but breaks under real users, real data or real billing. - You run a SaaS product and want AI features that hold up: agents, document search, data extraction or voice. WHAT I BUILD AI agents and workflows: multi-step agents with tool calling, state, retries and human handoff, plus custom MCP servers that connect Claude and other LLMs to your own tools and data. RAG and document AI: answers grounded in your documents with sources you can check, and extraction from PDFs, contracts and scanned files into structured data, with OCR where the documents need it. AI SaaS products and MVPs: authentication, multi-tenant data, Stripe subscriptions and credit metering, dashboards and admin panels, with the AI layer built in from day one. Voice AI: inbound receptionists and outbound calling agents on real telephony, with CRM write-back and warm transfer to a human. SELECTED PRODUCTS - Reviflow: AI review of construction drawings and chat with PDFs, with page-level citations. 5,000+ subscribers. - Chatley: 24/7 AI call answering with Twilio and CRM sync. Used by 1,000+ US businesses. - Kadastra: extraction from planning certificates and contract PDFs with FastAPI and AWS Textract OCR. 90% less manual legal review. - NOLMT: AI image and video generation SaaS with four workflows, credit metering and Stripe subscriptions. Live with paying users. - IDEO Lab: multimodal agent workspace that builds knowledge bases from PDFs, websites, YouTube and audio, with citation-grounded answers and token metering. - ValueBrand: AI brand analytics app, published on the Shopify App Store. - Voxr: outbound AI sales calls with sub-second latency, Deepgram transcription and per-lead state handling. RELIABILITY, NOT JUST A DEMO Evaluations for retrieval accuracy and hallucinations, guardrails, retries and fallbacks, latency and token-cost tuning, logging and monitoring. I'm currently running a hardening and reliability phase for a returning client after building their voice MVP. HOW I WORK - Written scope, milestones and fixed deliverables before any build starts. - Daily updates and a clickable demo every week. - Code in your repository and accounts from day one. No lock-in. - AI-assisted development with Claude Code and Cursor, with my own architecture, code review and tests. - Careful data handling, NDAs welcome, and experience building for regulated settings such as healthcare front-desk automation. - Long-term partnerships over one-off gigs: build, then harden, then grow. HOW PROJECTS START 1. A 30-minute scoping call. We agree what the product must do, the architecture and the fastest path to launch. 2. A one-week architecture sprint or production-readiness audit. You get a written plan, or a list of fixes ranked by risk. Starts at $500. 3. The build, in milestones. MVPs usually take 4 to 8 weeks. STACK AI: Claude API, OpenAI, Gemini, LangChain, LangGraph, MCP, embeddings, function calling, evals Backend: Python, FastAPI, Node.js, NestJS Frontend: Next.js, React, TypeScript, Tailwind Data: PostgreSQL, Supabase, Qdrant, pgvector, Pinecone, Redis Documents: AWS Textract, OCR, PDF parsing, structured extraction Voice: Twilio, Deepgram, ElevenLabs, LiveKit, Vapi, Retell Infra: AWS, Docker, Vercel, Stripe, CI/CD Send me what you're building and where it stands today. I'll reply within 24 hours with a technical direction, a realistic scope and a short Loom walkthrough.