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š Case Study: Building an Automated Local Lead Gen Engine Using n8n
Finding high-intent local business leads is a massive bottleneck for B2B agencies and developers. Manual prospecting wastes hours, and buying outdated cold lists ruins deliverability.
I built an end-to-end automation workflow using n8n that completely automates the pipeline, from raw discovery to AI-personalized outreach copies.
Here is a breakdown of how the architecture works and the stack behind it.
š” The Workflow Architecture
Hyper-Targeted Sourcing: The workflow programmatically scrapes physical businesses across the USA, mapping them out city-by-city and niche-by-niche.
The "No Website" Filter: It automatically flags businesses with no website or broken links. These are the highest-converting prospects for web agencies.
Data Enrichment & Storage: Extracts complete profiles (names, phone numbers, addresses, and ratings) and syncs them cleanly into Google Sheets and Airtable.
AI-Powered Personalization: The data is pushed to OpenAI to draft hyper-personalized outreach copies tailored exactly to that business's digital gaps.
Automated Reporting: Every morning, a compiled, qualified lead digest drops directly into my inbox.
š ļø The Tech Stack
Workflow Orchestration: n8n
Data Sourcing: Google Maps API & Web Automation
AI Layer: OpenAI
Database & CRM: Google Sheets & Airtable
šÆ What's Next?
The infrastructure is fully scalable and currently running on 100% autopilot. The next phase involves scaling this across deeper niches and building out bidirectional CRM integrations for seamless, end-to-end pipeline management.
Looking to automate your outbound infrastructure or scale your operations?
DM me here on Contra to discuss how we can build custom workflows for your business! š ļø
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Practical Ways I Use AI Every Day to Work Smarter
AI is not just a trend for me. It's part of how I work every day.
I use AI to speed up research, brainstorm ideas, draft content, review code, and automate repetitive tasks. It helps me move faster, think clearer, and focus more on high-value work.
My daily AI workflow usually looks like this:
1. Research
2. Ideate
3. Create
4. Review
5/ Automate
One thing Iāve learned:
AI does not replace real skills. It amplifies them.
The better your thinking, the better your prompts.
The better your prompts, the better your results.
AI wonāt take your job.
But someone using AI more effectively might.
How do you use AI in your daily workflow?
#AI #Productivity #SoftwareDevelopment #FullStackDeveloper #Automation #Tech #Innovation #LinkedInPost
Most lending businesses run on email threads, spreadsheets, and disconnected SaaS tools duct-taped together. That's where SBA Loans HQ started.
Brokers losing deals in their inbox. No pipeline visibility. Critical business logic living inside Zapier. Six months later, none of that was true anymore.
We built a full platform from scratch ā four user roles, a Kanban deal pipeline, automated document bundles, in-platform messaging, and a live analytics dashboard for leadership. Document collection that used to take days of back-and-forth now closes in hours.
AWS Textract pulls structured data from financial PDFs in seconds instead of 30 minutes. A multi-agent AI layer handles lead scoring, deal prioritization, and document analysis ā brokers see which deals are worth their time without reviewing everything by hand. Every third-party automation connector was replaced with a backend engine built in-house.
$33M+ in loans approved. 50+ lenders onboarded. 60% reduction in operational overhead. Six months, start to production.
Stack:Ā Next.js, Django, PostgreSQL, AWS, Multi-Agent AI, Textract, DocuSeal.
Congrats š„ Where'd you design your UI/UX?
AI-Powered B2B E-commerce Lookbook Generator
As an E-commerce specialist, I often see retail brands struggling to create high-end, "Retail Ready" lifestyle imagery for national buyers quickly. I built this Melius workflow to solve that. Itās an automated canvas that takes raw product images, processes them through specialized AI agents with tailored prompts, and outputs publication-grade B2B lookbook assets in minutes instead of weeks.
My Process Steps:
Input Node: Uploaded base product layouts (e.g., sustainable retail packaging).
Melius Agent Prompting: Configured a creative agent to analyze the asset and apply a high-end, editorial lifestyle background with strict whitespace rules.
Refinement Node: Passed the generated output through an upscaling and color-grading node to match national retail compliance and premium aesthetics.
Feedback on Melius:
Melius completely turns the thrash of traditional prompt-and-pray AI workflows into a structured visual canvas. Being able to see the node-by-node execution allowed me to tweak specific parameters instantly without losing the design direction. The speed at which it generates production-ready imagery is a game-changer for digital marketers and agency owners!
Wow this looks neat and premium! Did you design this using Melius?
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