AI-Driven Call Analytics for RCM
RCM provides communication software for self-storage operators managing hundreds of daily customer calls. Manual quality-assurance processes limited visibility into agent performance and delayed response improvements.
Challenges
- As call volume grew, RCM struggled to monitor service quality effectively. Insights were trapped in recorded audio, and manual sampling captured only a fraction of customer interactions.
The Solution
KnackForge implemented an AI-powered call analytics and insights platform for RCM to convert unstructured call data into real-time operational intelligence.
- Amazon S3, AWS Lambda, and Amazon ECS for automated transcription, summarization, and extraction of key call metrics including volume, duration, and sentiment.
- AWS Bedrock (Nova Pro) for conversational analytics, enabling administrators to query insights like call trends and averages in natural language.
- MongoDB with secure API access for centralized storage and integration with RCM’s reporting systems.
- RCM Portal Dashboards for real-time visibility into call volumes, peak hours, and staffing efficiency.
- Amazon CloudWatch and Amazon Inspector for observability, compliance, and IAM-based security monitoring.
The modular AWS architecture scales seamlessly, supporting new facilities and higher call volumes without additional operational overhead.
The Impact
- Achieved a 40% reduction in missed calls and over 50% faster access to insights through AI-driven chat analytics and improved peak-hour alignment.
- Improved response quality through automated feedback loops.
- Data-driven decisions enabled by real-time analytics dashboards.
RCM’s new call-analytics system transforms raw customer conversations into actionable intelligence, driving consistent, measurable service improvement.
Technologies Used:
- Amazon Transcribe
- Amazon Comprehend
- AWS Lambda
- Amazon QuickSight