Muhammad Haneef
AI Automation & Agentic AI Developer
New to Contra
Muhammad is ready for their next project!
Most ecommerce businesses don't have an inventory problem.
They have a manual-work problem.
Someone checks stock.
Someone updates another system.
Someone notices a product is running low.
Someone sends an alert.
Someone prepares a report.
And somehow, everyone calls this "operations."
I recently built an automated inventory system designed to remove much of that repetitive work.
The workflow connected inventory data, automation logic, alerts, reordering workflows, and reporting into one automated process using n8n, APIs, and AI.
The result?
→ 20+ hours of manual work saved
→ Automated inventory synchronization
→ Low-stock alerts
→ Reordering workflows
→ Automated reporting
But here's the part I think businesses often get wrong:
You don't need AI just because AI exists.
The valuable part isn't putting an LLM into every workflow.
It's identifying where a business is repeatedly spending human time, then deciding whether that problem is best solved with automation, AI, or a combination of both.
Sometimes the smartest AI system is the one that knows when NOT to use AI.
That's the approach I take with automation:
Find the bottleneck → design the workflow → automate the repetitive work → add AI where it actually creates value.
If your team is still copying data between systems, checking spreadsheets, sending repetitive alerts, or manually preparing reports, there's probably a better way to do it.
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A production-ready backend boilerplate for building scalable AI applications and agentic systems with authentication, databases, and AI integrations.
its like a pre-made template on which developers can build AI applications without writing the whole code from scratch.
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Built a production-ready observability platform for AI agents using FastAPI, PostgreSQL, Redis, LangGraph, React, and WebSockets.
The platform provides real-time visibility into agent execution, including traces, token usage, cost, latency, and errors.
Key capabilities:
• Real-time agent trace ingestion
• Execution tracking
• WebSocket-based live updates
• Token and cost monitoring
• Latency and error tracking
• Agent execution dashboard
• Instrumented research and customer-support agents
Tech: Python, FastAPI, PostgreSQL, Redis, LangGraph, React, Vite, WebSockets
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Built an automated inventory management workflow that synchronizes inventory data, monitors stock levels, triggers alerts, and supports reorder workflows and reporting.
The automation eliminated repetitive manual inventory operations and saved the store 20+ hours.
Capabilities:
• Inventory synchronization
• Low-stock alerts
• Reorder workflows
• Automated reporting
• Business process automation
Tech: n8n, AI automation, APIs, workflow automation
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