Driving Innovation
Rubiscape's Impact in the
Customer Service Team
Solutions build with Rubiscape
Implement Rubiscape’s AI-enabled Solutions! Geared for the future!
Listening In: Insights with Audio Analytics
Beyond speech, audio reveals emotions, behaviors, and trends, driving better decisions.

Goal
- To identify anomalies in customer-operator interactions.
 
- To identify factors affecting customer satisfaction .
 
- Behavioral analysis of Customer and Operator.
 
- To identify anomalies in customer-operator interactions.
 - To identify factors affecting customer satisfaction .
 - Behavioral analysis of Customer and Operator.
 
Technique
- Audio processing, Audio Diarization, Speech to Text, Text translation, Sentiment Analysis, Topic Modelling.
 
- Audio processing, Audio Diarization, Speech to Text, Text translation, Sentiment Analysis, Topic Modelling.
 
Impact
- Improvement in CSAT and reduced customer complains.
 
- Identify most frequently inquired new requirements by the customer.
 
- Early warning for customer issues and proactive corrective actions.
 
- Better operator performance
 
- Improvement in CSAT and reduced customer complains.
 - Identify most frequently inquired new requirements by the customer.
 - Early warning for customer issues and proactive corrective actions.
 - Better operator performance
 
Delight Purchase: Mastering Sales & Service
Exceed expectations, build loyalty, and fuel repeat business with exceptional after-sales support.

Goal
- To represent the root cause of failures.
 
- To determine the time for first failure of an equipment part and forecast number of future breakdown calls for that part.
 
- To identify interdependency of part failures.
 
- To represent the root cause of failures.
 - To determine the time for first failure of an equipment part and forecast number of future breakdown calls for that part.
 - To identify interdependency of part failures.
 
Technique
- Statistical Analysis, Root cause Analysis, Reliability Analysis, Time Series Forecasting, Visualization.
 
- Statistical Analysis, Root cause Analysis, Reliability Analysis, Time Series Forecasting, Visualization.
 
Impact
- Based on root causes of failure, location/manufacturer wise strategies can be planned to avoid early failure.
 
- Reduction in number of breakdown calls and associated cost.
 
- Early warning breakdown calls helps in taking preemptive measures.
 
- Identified sequence of patterns for failure of parts, helps in preventive actions.
 
- Based on root causes of failure, location/manufacturer wise strategies can be planned to avoid early failure.
 - Reduction in number of breakdown calls and associated cost.
 - Early warning breakdown calls helps in taking preemptive measures.
 - Identified sequence of patterns for failure of parts, helps in preventive actions.
 
See-Through Repairs: AI Detects Damage
Pinpoint defects faster, save costs, and optimize production with intelligent damage detection.

Goal
- To identify and classify damages such as scratches, dents or cracks in vehicles.
 
- To allow early identification of damages and timely maintenance interventions.
 
- To enable automated and accurate inspections for insurance claims.
 
- To identify and classify damages such as scratches, dents or cracks in vehicles.
 - To allow early identification of damages and timely maintenance interventions.
 - To enable automated and accurate inspections for insurance claims.
 
Technique
- Image augmentation, Image processing, Image classification, Object detection, Visualization.
 
- Image augmentation, Image processing, Image classification, Object detection, Visualization.
 
Impact
- Accelerated claims processing, reducing delays and administrative burden.
 
- Reduced post-purchase repair costs, to enhance ownership experience.
 
- Enhanced brand image, to attract and retain customers.
 
- Boosted customer satisfaction and loyalty.
 
- Accelerated claims processing, reducing delays and administrative burden.
 - Reduced post-purchase repair costs, to enhance ownership experience.
 - Enhanced brand image, to attract and retain customers.
 - Boosted customer satisfaction and loyalty.
 
Unveiling Loyalty: Predict Customer Lifespan
AI models pinpoint high-value customers, driving targeted engagement and long-term growth.

Goal
- To identify high, medium, and low-value customer segments.
 
- To provide personalized offers and experiences to customers.
 
- To allocate resources efficiently to businesses for targeting customers with the highest CLV potential and predict customer churn.
 
- To identify high, medium, and low-value customer segments.
 - To provide personalized offers and experiences to customers.
 - To allocate resources efficiently to businesses for targeting customers with the highest CLV potential and predict customer churn.
 
Technique
- Feature Engineering, Segmentation Techniques, RFM Analysis, Clustering and classification modeling, Visualization.
 
- Feature Engineering, Segmentation Techniques, RFM Analysis, Clustering and classification modeling, Visualization.
 
Impact
- Guided resource allocation, marketing strategies, and customer service efforts.
 
- Offering cross-selling and upselling opportunities to customers with CLV potential.
 
- CLV helps businesses identify risks associated with over-reliance that encourages diversification and risk management strategies.
 
- Guided resource allocation, marketing strategies, and customer service efforts.
 - Offering cross-selling and upselling opportunities to customers with CLV potential.
 - CLV helps businesses identify risks associated with over-reliance that encourages diversification and risk management strategies.
 
Do even more with Rubiscape
AI-driven organisations around the world use Rubiscape to solve their most pressing business problems.

Drag, Drop, Discover: 
 Insights Made Simple.
Dive deep into your data, create stunning visuals, and gain actionable insights with ease.
Learn More
Learn More

Build, Deploy, Manage: 
Streamline AI Workflow.

Wrangle, Blend, Analyze: 
 Data Orchestration Refined.



