AI-Powered Conversation Summaries in GoHighLevel

A sales team managing thousands of contacts in GoHighLevel was spending too much time reviewing long SMS and email histories before following up with leads.

I built an automated AI summarization workflow inside GHL using tag-based triggers. The system collects conversation data, generates either a recent activity summary or a full conversation summary, and saves the result directly inside the contact record.

It also compares new activity with previous summaries to avoid unnecessary duplication.

Result: Sales reps can understand the full conversation context much faster without reading every message. The workflow saves hours of manual review, improves response speed, and scales across large contact volumes.

Tools: GoHighLevel • AI • Workflow Automation • CRM Automation • API Logic

Impressive solution to the time-draining review of long SMS and email histories - your tag-based triggers and automatic conversation summaries will let reps jump straight into meaningful follow-ups. Scaling that across thousands of contacts is a huge productivity win.

A booking is not an island.

A nervous pup, a customer, a changed appointment, a reminder—these shouldn't become disconnected pieces of information.

This 54-second walkthrough shows the knowledge graph in The Wagging Wagon. Follow Teddy from his booking to his saved note, then inspect a demo agent journey: what it noticed, what changed and whether owner approval was needed.

Recorded actions and inferred relationships are labeled separately. That distinction matters when a person is trusting an automated workflow.

I'm Olanrewaju Agaun, founder of Ubunex. I enjoy building systems whose behavior people can understand—not just interfaces they can admire.

Explore the app: https://wagging-wagon.lovable.app/

Looking for a developer who cares about both product design and AI workflows? Message me here on Contra.

The Wagging Wagon was built with Lovable. Fictional demo data, seeded agent replay and simulated SMS.