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🚀 Recent Project: GoHighLevel Automation for Event Rentals
Built a 14-stage email automation system in GoHighLevel with smart workflows connected to Xero payment status. The setup automated confirmations, reminders, billing follow-ups, and post-event communication, helping reduce manual support and improve client experience.
Role: Lead Copywriter & CRM Automation Architect
XerogohighlevelautomationautomationexpertGo High LevelEmail AutomationAI AutomationBusiness Workflow Automation
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Related posts
GoHighLevel Architectural Review Confirmation & Notification Workflow
Engineered an automated architectural review workflow in GoHighLevel to capture incoming submission forms, dispatch automated email confirmations to applicants, and alert internal review teams immediately.
Key Deliverables & Setup:
• Form Trigger Ingestion: Automatically captures new submissions from multiple architectural review forms.
• Applicant Confirmation Emails: Triggers personalized confirmation emails to notify clients that their submission was received.
• Internal Alerts & Notifications: Sends real-time team notifications to ensure timely review and approval routing.
Results & Impact:
• Guarantees instant client communication upon request submission.
• Streamlines internal operations and removes manual follow-up delays for review teams.
AI Assistant Using Your Business Knowledge Base — RAG on Your Documents
THE PROBLEM
Q&A bots break down when knowledge lives in documents: a 100-page manual has no "questions" to match, it can't fit into a prompt, and generic chatbots hallucinate instead of admitting what they don't know.
THE SOLUTION
A RAG (Retrieval-Augmented Generation) knowledge base: documents are split into meaningful chunks, embedded into a vector index, and the assistant answers from the right sections — by meaning, not keywords.
Any format as-is: PDF, DOCX, TXT, Markdown — 100+ pages is fine
Answers grounded in YOUR documents — it says "I don't have that information" rather than inventing
Source references — every answer shows which document and section it came from
Runs on your infrastructure — documents never leave your control
One command to re-index after updating documents — documented, no programmer needed
LIVE DEMO
Ask it about my products, pricing, deployment and support — it answers from 6 real documents with sources:
https://kb-assistant-demo.dvc-ai.workers.dev
The 'I don't have that information' line is the part most RAG builds skip, and it's the one that matters. How do you set the cutoff? On mine, a fixed similarity threshold broke once I filtered results by user role. Scores shifted and it refused questions it could answer.
Automated a manual Google Sheets → Slack workflow to eliminate repetitive data entry and give the team instant notifications.
Previously, new data had to be manually checked, processed, and shared across the team — slow and easy to miss. I built a Make.com scenario that:
Watches Google Sheets for new/updated rows
Processes and routes the data through a router based on conditions
Creates corresponding Trello cards for task tracking
Logs processed records back to Google Sheets
Sends real-time Slack notifications so the team is instantly updated
Result: What used to be manual checking and updating is now fully automated — saving hours weekly and removing room for human error.
Tools: Make.com, Google Sheets, Trello, Slack
wow love this