IndustryAWS
ServicesCloud Managed Services
We made a visible and
measurable impact to our
client's business
Query accuracy based on user feedback
90%
Automated 70% of common inquiries
70%
Handled simultaneous users during peak hours
750+
Response time under
3 seconds
About the Client
A leading software provider looking to improve customer support efficiency and enhance user satisfaction. Their goal was to implement an AI-powered solution to handle growing user demands and provide faster, more accurate responses.
The Problem
The company faced increasing challenges with its manual support system:
- Slow Response Time: Delayed responses led to customer frustration and missed opportunities.
- Inconsistent Answers: Manual handling caused variations in support quality.
- Scalability Issues: The system struggled to manage high user volumes during peak hours.
- High Workload: Support teams were overwhelmed with repetitive queries.
Our Approach
Lauren Group designed and implemented an AI-driven chatbot using AWS to enhance support efficiency:
- Amazon Bedrock: Powered the chatbot with advanced AI models for natural language understanding.
- Amazon EC2: Hosted the chatbot for reliable and scalable performance.
- Amazon S3: Provided secure storage for chatbot interactions and user data.
- ChromaDB: Managed real-time user data for personalized responses.
- AWS CloudWatch and CloudTrail: Monitored performance and ensured seamless operations.
- Automation: Reduced manual workload by handling 70% of common inquiries.
Tech Stacks Used
Amazon Bedrock
Amazon EC2
Amazon S3
ChromaDB
AWS CloudWatch
AWS CloudTrail
The Result
- 90% Accuracy: Delivered highly accurate responses based on user feedback.
- 750+ Users: Handled high traffic without performance drops.
- 70% Automation: Reduced manual workload and improved efficiency.
- Faster Response: Achieved average response time under 3 seconds.
- Enhanced Customer Satisfaction: Faster, more accurate support improved user experience.