I build practical AI-powered automation workflows and AI agent solutions that connect AI models, business tools, APIs, and data to reduce repetitive work and improve productivity.

I am currently focused on strengthening my practical skills through hands-on automation projects while preparing to work on real-world AI automation solutions.

• 🤖 Focused on AI Automation, AI Agents, and Business Process Automation
• ⚙️ Building workflows with n8n, Make.com, and Zapier
• 🧠 Working with OpenAI, Claude, Gemini, RAG, and MCP
• 🔗 Integrating applications using REST APIs, Webhooks, JSON, and OAuth
• 📚 Continuously learning, building, testing, and improving practical automation solutions
• 🌍 Open to remote, hybrid, local, and international opportunities
• 📍 Based in Dhaka, Bangladesh

n8n • Make.com • Zapier

AI Agents • OpenAI • Claude • Gemini • RAG • MCP • Retell AI / Voice AI

REST APIs • Webhooks • JSON • OAuth / API Authentication • Web Scraping

Google Sheets • Gmail • Google Drive • CRM Automation • Lead Generation • Customer Support Automation

Supabase • Airtable • Apify • ElevenLabs • FFmpeg

Currently, I am focused on:

• Building end-to-end AI automation workflows
• Developing practical AI agent solutions
• Connecting AI models with external tools and business systems
• Improving API, webhook, RAG, and MCP-based integrations
• Documenting and publishing my automation projects on GitHub

An AI voice receptionist prototype developed as a hands-on automation project using Retell AI, MCP, and n8n.

The system connects a voice agent with multiple automation tools to handle course-related queries and business workflows.

Key Capabilities:

• Course search and class schedule checking
• Lead capture
• Consultation booking with Google Calendar
• Email confirmation
• FAQ knowledge-base support
• Human escalation request handling
• Conversation logging

Tech Stack:
Retell AI • MCP • n8n • Google Sheets • Google Calendar • Gmail • REST APIs • Webhooks

Project Highlights:

• 9 documented n8n workflows
• Multiple MCP-connected automation tools
• Voice AI + workflow automation integration
• Architecture diagram and workflow screenshots
• Sanitized public workflow files
• Documented limitations and future improvements

🔗 View Project Repository →

This is a learning and portfolio project developed as part of an AI Automation assignment and is not an official Ostad Academy production system.

An AI-powered news research automation developed as a hands-on project using n8n, GNews API, OpenRouter, and Google Sheets.

The workflow accepts a topic and article count through a webhook, researches and analyzes current news articles with an LLM, stores structured results, and returns the Top 3 stories ranked for LinkedIn relevance.

Key Capabilities:

• Topic-based news collection through GNews API
• Per-article AI summarization and research
• Practical key takeaway extraction
• AI news category classification
• LinkedIn Worthiness Score from 1–10
• Structured AI output validation
• Google Sheets research storage
• Top 3 article ranking by score and recency
• JSON API response through webhook

Tech Stack:
n8n • GNews API • OpenRouter • Google Sheets • Webhooks • JavaScript • Bruno

Project Highlights:

• End-to-end webhook-driven research workflow
• Configurable LLM through OpenRouter
• Structured Output Parser for consistent AI responses
• Custom JavaScript ranking logic
• Architecture diagram and workflow screenshots
• Sanitized public n8n workflow
• External workflow execution demo
• Documented setup, limitations, and future improvements

🔗 View Project Repository →

An end-to-end assignment collection and validation automation built with Make.com, Google Forms, Google Sheets, Google Drive, Google Docs, and Gmail.

The system processes student assignment submissions, cleans and validates submission data, detects duplicates, routes valid and invalid submissions, organizes records and folders, sends automated notifications, and updates final submission status in Google Sheets.

Key Capabilities:

• Google Forms-based assignment submission intake
• Google Sheets-triggered Make.com automation
• Data cleaning and normalization
• Duplicate submission detection
• Valid, invalid, and duplicate submission routing
• Student-wise Google Drive folder creation
• Automatic Google Docs submission summary generation
• Student confirmation emails
• Instructor notification emails
• Submission status tracking in Google Sheets
• On-time / late status tracking from submission data

Tech Stack:
Make.com • Google Forms • Google Sheets • Google Drive • Google Docs • Gmail

Project Highlights:

• End-to-end automated assignment processing workflow
• Three-route validation and submission handling
• Automated folder and document creation
• Student and instructor email notifications
• Centralized submission tracking in Google Sheets
• Architecture diagram and implementation documentation
• Sanitized public Make.com blueprint
• External workflow execution demo
• Documented test results and current implementation limitations

🔗 View Project Repository →

An end-to-end AI-powered real estate automation system built with n8n, Apify, Airtable, OpenAI, and MCP.

The system automatically collects Dubai rental property listings from PropertyFinder through Apify, cleans and structures the scraped data with AI, stores the listings in Airtable, exposes the database through an MCP Server, and allows an AI assistant to answer natural-language questions about available properties.

Key Capabilities:

• Scheduled Dubai real estate listing collection
• PropertyFinder scraping through Apify
• AI-powered property data cleaning and structuring
• Structured Output Parser validation
• Airtable listing storage and upsert by Listing URL
• MCP Server with 7 specialized property tools
• Budget-based property search
• Location-based listing search
• Latest listing retrieval
• Cheapest property lookup
• Listing count queries
• Full property list retrieval
• Natural-language property queries through an AI Assistant

Tech Stack:
n8n • Apify • Airtable • OpenAI • MCP • HTTP Request

Project Highlights:

• Three connected n8n workflows
• Automated scraping and structured property storage
• Seven Airtable-backed MCP tools
• AI Assistant connected through MCP Client
• Natural-language budget and location filtering
• Real chat-query examples with actual listing results
• Architecture diagram and workflow screenshots
• Sanitized public n8n workflow exports
• External demo video and Airtable database
• Documented setup, implementation notes, limitations, and cost estimation

🔗 View Project Repository →

• 🌐 Portfolio: automation-ai-jamil.lovable.app
• 💼 LinkedIn: S. M. Jamilur Reza Razib
• 📧 Email: jamilur0101@gmail.com