AI-Powered QC KPI Platform for Call Intelligence and Quality Control

AI-Powered QC KPI Platform for Call Intelligence and Quality Control

The company wanted a centralized quality control platform to bring call recordings, lead activities, and deal information together while reducing the manual effort involved in reviewing sales conversations.

Business Challenge

The client managed customer interactions and sales information across three separate business platforms. This fragmented setup created challenges in monitoring conversations, evaluating performance, and maintaining consistent quality standards.

Key challenges included:

• Fragmented Business Data: Call recordings, lead activities, and deal information were stored across three different platforms.
• Manual Call Reviews: Quality control teams had to listen to recordings individually to evaluate conversations.
• Inconsistent Evaluation: Manual reviews made it difficult to maintain standardized summaries and outcome classifications.
• Limited Call Intelligence: Identifying customer sentiment, conversation quality, and call outcomes required additional effort.
• Scattered Reporting: Teams lacked a centralized view of call quality and performance indicators.

Suretek's Solution

Suretek Infosoft developed an AI-powered QC KPI platform that consolidates business data and automates conversation analysis using Google Gemini AI.

Key Features:

• Centralized Data Integration: Integrated three business platforms to bring call recordings, lead activities, and deal information into one centralized system. This provided quality control teams with a unified view of customer interactions and related business activities.
• Gemini AI-Powered Call Analysis: Integrated Google Gemini AI to analyze recorded conversations and generate meaningful insights, including:
  • Sentiment Analysis: Identifies the sentiment expressed during customer conversations.
  • Automated Call Summaries: Generates concise summaries of recorded interactions.
  • Outcome Classification: Categorizes conversations based on their outcomes for standardized quality reviews.
• Python-Based Automation: Developed a Python workflow to process call recordings, coordinate data collection, and integrate information from all three business platforms. This reduced the need for repetitive manual data handling and supported a consistent analysis process.
• Centralized QC Review Dashboards: Developed centralized quality control dashboards to help teams review AI-generated summaries, conversation classifications, and associated business information from one place.
• Standardized Quality Control: Introduced structured call summaries and outcome categories to make conversation reviews more consistent and easier to evaluate across the organization.

Impact Delivered

The platform transformed the client's call quality review process from manual recording checks into a centralized, AI-assisted workflow.

• Reduced Manual Call Reviews: AI-generated summaries reduced the need to listen to every recording in full.
• Faster Conversation Analysis: Gemini AI automated sentiment analysis, summarization, and outcome classification.
• Unified Business Information: Data from three platforms became accessible through a centralized QC platform.
• Standardized Evaluations: Consistent summaries and outcome categories improved the structure of quality reviews.
• Improved Visibility: Centralized dashboards made call information and related business activities easier to review.
• Streamlined Operations: Python automation reduced repetitive data processing and integration work.

Technologies Used

To develop the AI-powered QC KPI platform, the following technologies were used:

• AI & Machine Learning: Google Gemini AI for conversation analysis, sentiment detection, automated summaries, and outcome classification.
• Backend & Automation: Python for recording processing, workflow automation, and data integration.
• API Integration: Connected three business platforms (CallerRead, Skywave CRM, and Fourth CRM) to consolidate call recordings, lead activities, and deal information.
• Dashboard & Reporting: Centralized QC dashboards for conversation reviews and quality monitoring.

Why It Matters

Customer conversations contain valuable insights into sales performance, customer satisfaction, and business outcomes. However, manually reviewing large volumes of recordings can limit how quickly organizations identify patterns and evaluate quality.

By combining Gemini AI with Python-based automation and centralized data integration, Suretek helped demonstrate how businesses can turn customer conversations into structured, actionable insights while making quality control more efficient.

Conclusion

Suretek Infosoft delivered an AI-powered QC KPI platform that brought call recordings, lead activities, and deal data from three business platforms into one centralized system. With Gemini AI-powered conversation analysis and Python-based workflow automation, the solution replaced repetitive manual call reviews with standardized summaries, sentiment insights, and outcome classifications.

The project demonstrates how AI integration and automation can help businesses improve call intelligence, streamline quality control, and make better use of customer interaction data.