Automated Sales Operations with GHL

We replaced the traditional SDR team with AI Agents. By integrating NLPEARL with GHL, we automated the entire sales floor from cold calling to meeting reminders resulting in zero admin time and tripled attendance rates.

About the project

Scaling an outbound sales team typically requires hiring more humans. This client took a different approach: Synthetic Labor. We engineered a fully autonomous "Voice Operations Center" using NLPEARL agents orchestrated by Make.com. This system not only dials leads and books appointments but also manages the critical "Show Rate" through intelligent reminder calls.

Date:

Jan 11, 2026

Client:

Anonymous

1. The Master Architecture

The system is designed as a "Hub and Spoke" model. The Central Nervous System (Make.com) connects the CRM, the Voice Agents, and the Human Operations team.

High-level data flow showing the central orchestration by Make.com.
The Agent Fleet configuration in NLPEARL, showing the Outbound and Reminder agents ready for deployment.

2. Workflow A: The Outbound Qualifier

The Goal: Eliminate "cold calling" for human closers. The Logic: A new lead triggers an immediate call. The AI navigates the conversation, qualifies the prospect, and books the meeting directly.

The 'Traffic Light' decision tree showing success vs. failure paths.
The complex Make.com scenario that handles fetching the lead, triggering the call, and parsing the webhook result.
The CRM Automation that listens for the 'Booked' tag and instantly moves the Opportunity to the 'Interested' stage.

3. Workflow B: The "Zero-Flake" Reminders

Booking the meeting is only half the battle. We deployed a ruthless "Reminder Agent" to minimize no-shows at 24h, 12h, and 1h intervals.

The timeline logic ensures leads are touched 3 times before a meeting.
The multi-stage reminder automation monitoring the GHL Calendar.

The "No-Show" Safety Net

If a prospect misses the call, the system immediately attempts to recover them.

Logic to detect missed appointments and trigger the recovery agent.

The specific script and configuration for the No-Show recovery agent.

4. Workflow C: The AI Feedback Loop (QA)

To ensure quality without listening to hours of audio, we built an automated "Quality Assurance" pipeline. Every call is transcribed, analyzed, and posted to Slack.