Hello, I'm Malik.
Ten years of software engineering, 210+ projects at 5.0 on Fiverr, the last few years shipping LLM systems into real business software. Karachi, UTC+5.
Read about me →10 years of software engineering; the last few shipping LLM systems into real business software. Not a chatbot that answers and stops.
Pick a problem. This is the shape of the read I'd send back within 24 hours.
RE: Invoices & documents
RE: CRM ↔ accounting sync
RE: An assistant on your own data
RE: An undocumented or legacy API
I've spent ten years building software for people who need it to work on Monday morning, not just in the demo. Two hundred and ten-plus projects with a 5.0 average rating on Fiverr, and enough production incidents to know what actually matters: honest scoping, boring reliability, and code you still own when I'm gone.
For the last few years that has meant putting LLMs to work inside real business systems — agents that read documents and take actions, assistants that answer with sources, integrations between tools that were never meant to talk. I like the unglamorous parts: retries, rate limits, logging, the monitoring that keeps a system running while you sleep.
I work from Karachi with clients in the US, UK, EU, Australia and the Middle East, overlapping US mornings and EU afternoons. You'll get written updates without asking, a realistic estimate, and a straight answer — including "you don't need AI for this" when that's the truth.
A short scoping call before any estimate. I would rather tell you the project is simpler than you thought than take a bloated budget.
Error handling, logging, and monitoring from day one, not after something breaks. Realistic estimates, fixed scope, clear milestones, no surprise invoices.
Documented, structured, yours. No lock-in, no black box, and support after delivery — I don't disappear at handover.
One you can open. Two I can only describe: client work stays private, so I show the shape of it instead.
01 AI operations agent live
Paper in. Actions out.
An AI operations agent that reads supplier invoices and customer emails, checks them against the company's own systems, and does the work: bills in QuickBooks, tickets in the helpdesk, a line in Slack.
02 Client work · Logistics company
Refunds, partial payments, and reconciliation handled automatically. Has reconciled cleanly since launch without manual fixes.
No public link — client work
03 Personal tooling
Fetches listings, scores them against a profile, drafts proposals with an LLM, schedules follow-ups. FastAPI + SQLite + local dashboard, tested end to end.
No public link — personal tooling
Systems that do the work. Not a chatbot that answers and stops.
Systems that do the work: process documents, qualify leads, research, draft, classify, and take real actions inside your tools.
LLMs wired into your CRM, database, admin panel, Google Workspace, Slack, Notion, HubSpot, Shopify, or a legacy system nobody wants to touch.
Third-party, undocumented, and legacy SOAP APIs. Webhooks, OAuth flows, rate-limited endpoints, data syncs between systems never designed to talk.
Trained on your own data, answering with sources so output is verifiable instead of confidently wrong.
The APIs, queues, schedulers, and pipelines underneath all of the above. Built to survive production, not just a demo.
Multi-domain sending, SPF/DKIM/DMARC, custom tracking domains, warmup, API-level integration.
Full products and internal tools: React and Next.js front ends on Python or Node back ends, admin panels, dashboards, and the APIs underneath. Ten years of shipping software that is documented, structured, and yours.
React Native and Flutter apps that share the API, auth, and data of your web product: iOS and Android from one codebase, with the backend built to match.
AI agents · Web apps · Mobile apps · API integration · RAG · LLM tool use · FastAPI · Node.js · Next.js · PostgreSQL · Redis · Docker · AWS · Stripe · HubSpot · Shopify · webhooks · OAuth2 · SOAP · MCP servers · evals · email deliverability
The tools I reach for, and the older ones I still add AI to.
Send me the problem. Short scoping call first — I would rather tell you the project is simpler than you thought than take a bloated budget.