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NetSuite Implementation, Data Migration & Integration Project
Worked on NetSuite Implementation migration and integration support projects involving customer/vendor imports, financial data handling, workflow setup, Bank integration reporting optimization, and external system integrations. Contributed to successful ERP delivery projects completed implementation work and positive client feedback.
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AI-Powered CRM Built To Capture And Qualify Leads
Built a lead qualification and CRM workflow that captures inquiries, filters serious prospects, and helps the team follow up faster.
❌ Before Automation
→Leads were coming in, but the process was not clean.
→New inquiries had to be checked manually.
→Some leads needed a quick follow-up.
→Others were not the right fit.
The team had no easy way to separate serious prospects from low-quality leads.
This created 4 problems:
• Slow lead response
• Manual lead checking
• Missed follow-ups
• No clear CRM visibility
Better short version for design:
✅ After Automation
We built an AI-powered lead qualification and CRM system.
The system captures new leads, verifies the information, qualifies prospects, and sends the right data to the CRM. This gives the team a cleaner pipeline and faster follow-up process.
Now the business can see:
• Who the lead is
• What they need
• How serious they are
• Where they are in the pipeline
• What action should happen next
See The Full Workflow here
⚡Another Recent Project: Xero OAuth2 Automation for a UK Event Hire Business
Built a complete automation system connecting Xero, GoHighLevel, and the client’s booking platform using Make.com and OAuth2 integration.
The workflow automates invoice creation, cancellation credit notes, and payment syncing across all platforms, removing the need for manual accounting tasks.
Role: Automation & API Integration Specialist
Case Study: The Autonomous B2B Lead Generation Engine
Role: AI Systems Architect & Developer
Tools Used: n8n, SerpAPI, Google Sheets API, Gmail API
Deliverable: Fully automated lead scraping and cold outreach pipeline.
🛑 The Problem: The "Dead List" Dilemma
For B2B companies, manual lead research is the biggest bottleneck to scaling revenue. Most businesses waste 15+ hours a week manually scraping Google Maps for local prospects, or worse, they buy outdated lead lists filled with dead websites and disconnected phone numbers.
The goal of this project was to build a system that completely eliminated manual prospecting. The system needed to autonomously locate high-intent local businesses, extract their contact data, format it perfectly into a CRM, and initiate personalized outreach—all without a single human click.
🏗️ The Solution & Architecture
I engineered the Growth & Outreach Engine using n8n to connect live search data directly to an automated email pipeline.
The Workflow Pipeline:
Live Data Extraction: Utilizing SerpAPI, the agent runs localized, niche-specific queries (e.g., "coaching institutes in Texas") to pull real-time, verified business data.
Data Filtration & Formatting: The system filters out incomplete profiles and strictly isolates high-value contact points (verified phone numbers and emails).
CRM Injection: Extracted data is autonomously injected into a centralized Google Sheet, acting as a live database.
Outreach Deployment: The pipeline triggers an Automatic Email Sender via Gmail to draft and send highly targeted introductory emails to the newly acquired prospects.
🚧 Overcoming Technical Roadblocks
Building a prototype is easy; building a resilient system requires overcoming the chaos of real-world internet data. During development, two major roadblocks threatened the pipeline:
The "Dead Link" Trap: Initially, the scraper targeted business websites to extract data. However, local markets are plagued by 404 errors, aggressive Cloudflare anti-bot walls, and missing domains, which stalled the automation.
The Fix: I re-engineered the logic to bypass fragile website scraping entirely, pivoting the extraction focus to verified Google Business phone numbers and directory emails, ensuring a 99% data success rate.
The Spreadsheet Crash: Google Sheets natively misinterprets international phone numbers (like +1 or +91) as mathematical formulas, throwing massive #PARSE! errors that corrupt the database.
The Fix: I injected a custom string conversion node—adding a hidden single quote (') via an n8n expression (='{{ $json.phone }})—forcing the CRM to accept the raw text flawlessly.
📈 The Results & Impact
What started as a complex engineering challenge is now a high-speed, invisible growth engine.
Hours Saved: Eliminated 15+ hours per week of manual data entry and prospecting.
Data Accuracy: Achieved a near 100% success rate in pulling active, verified contact information rather than outdated lists.
Speed to Market: The system can scrape, format, and initiate outreach to 50+ localized leads in under 2 minutes of execution time.
🤝 Why This Matters For Your Business
True automation is not about how many AI models you can chain together; it is about building resilient systems that survive real-world data and actually scale your revenue.
If your team is still manually hunting for leads or drowning in data entry, let’s build a custom Growth Engine for your business.
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