A mid-scale fintech processing high volumes of CRM-driven sales data faced a common scaling bottleneck: the gap between process definition and human execution. With a rapidly growing sales team, manual follow-ups were inconsistent, SLAs were breached, and CRM accuracy was degrading, leading to poor forecasting.
Valid leads were slipping through cracks due to manual follow-up failures. The team was unable to track if a high-intent lead had been contacted within the 'Golden Window'.
Inaccurate data entry by humans led to poor forecasting. Managers had to micromanage reps to update statuses, creating friction and reducing selling time.
We deployed two distinct systems to handle quality assurance and active execution.
We deployed an automated QA layer that listens to 100% of sales calls. It transcribes, analyzes, and extracts key data points to verify against CRM entries.
An event-driven engine that monitors SLAs in real-time. It ensures the process is followed without human micromanagement by handling the "nudge" logic.
Sales rep completes a call. The audio is instantly captured by the QA Intelligence system.
AI analyzes the transcript for sentiment, objections, and next steps. It compares this to CRM data.
If the rep misses a follow-up task creation, the Actions Engine creates it automatically.
The engine watches the task. If the deadline approaches, it alerts the rep to act.
By moving from human-dependent compliance to system-enforced compliance, the operations shifted from reactive to proactive.
The Boundary Principle