Abdul H.

I build AI-powered full-stack systems: the agents and RAG pipelines, plus the product around them, running in production. Recent work: a self-hosted multi-agent ops platform on local LLMs, a multi-tenant AI platform with 11 user roles and 15+ integrations, and document Q&A with citations. Getting an agent to work once is easy. The hard part is making it accurate enough that you stop double-checking it, and that's where I spend my time. RECENT PRODUCTION WORK • Self-hosted AI operating system for a company's operations. Multiple agents run the day-to-day on the client's own hardware with local LLMs, so no data leaves their network. They triage every mailbox, extract line items from documents, draft follow-ups, and send the CEO a daily summary that a second agent checks figure by figure. Python agent services behind a NestJS app, with durable job queues and a full audit trail. It replaced manual email triage, spreadsheet pricing and a separate payment tracker. • AI voice agent for a consumer brand. Handles inbound support calls end to end: identifies products across a 100+ item catalog, checks warranty, logs tickets and escalates to a human. A 10-node graph with multi-model routing brought the average call cost to $0.27. • Document intelligence platform (live, B2B). Teams upload documents and ask questions in plain English, getting answers with citations. OCR and RAG over multi-tenant workspaces with fine-grained access control. • AI insights platform (live, B2B). Several AI agents working side by side, including research and meeting analysis, inside a multi-tenant app with 11 user roles and 15+ integrations. I also build automations in n8n and Make. My own n8n build, an Instagram DM booking agent, answers DMs with Claude, books appointments into Google Calendar and hands conversations to a two-way Slack inbox (11 workflows; video walkthrough in my portfolio). WHAT AI AGENTS CAN TAKE OFF YOUR PLATE • Sorting your inboxes, drafting replies and following up until things get done • Pulling data out of PDFs, scans, invoices and spreadsheets • Keeping deals, projects and deadlines moving, and flagging what's stuck • Daily and weekly summaries of what happened and what needs you • Answering questions over your documents and internal knowledge, with sources • Handling phone calls, support and lead qualification with voice agents HOW I MAKE THEM RELIABLE • Each agent has one clear job, clear handoffs, and a log of why it did what it did • The AI handles language; code handles numbers, so figures are never made up • Approval steps where a mistake is costly, full autonomy where it isn't • Every change is tested against your real past data before it touches live work BUILT LIKE PRODUCTION SOFTWARE, NOT A DEMO • Full-stack: the agents plus the product around them, from the dashboard your team uses to roles, permissions and billing • Durable background jobs and queues, so long-running work survives restarts and retries safely • Integrations with Google Workspace, Microsoft 365, CRMs and project tools through their APIs • Multi-tenant architecture, audit trails and access control for teams handling sensitive data • Docker deployments with zero-downtime updates and rollback, in the cloud or on your own servers Clients mention clear communication and thorough documentation and walkthroughs. You'll always know what was built, how it works, and why. Stack: Python, TypeScript, LangGraph, LangChain, FastAPI, Next.js, React, NestJS, Node.js, PostgreSQL, pgvector, Prisma, Redis, Claude, OpenAI, Ollama, ElevenLabs, Twilio, n8n, Make, Microsoft Graph, Docker, AWS. Tell me which part of your week eats the most time and what tools you use today. That's enough for me to tell you what's worth automating first, and whether it's a two-week build or a two-month one.