Case Study

Advanced HRMS Chatbot using AWS GenAI for Enhanced User Interaction for a Software Company

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Industry 

Software and IT

Expertise 

Amazon Bedrock, Amazon S3, Amazon OpenSearch, Amazon Translate, Amazon Comprehend, AWS Lambda, Amazon API Gateway, AWS IAM, AWS CloudTrail, Amazon CloudWatch

Offerings/solutions 

Bi-lingual chatbot on Amazon Bedrock, integrating AI and automation for seamless, accurate user interactions, boosting efficiency and user satisfaction.

About the Client

Argenbright Innovation Lab, aligned with Argenbright Holdings’ mission, pioneers deep tech for societal well-being. They specialize in advancing frontline services and hourly wage workforce through advanced tech, aiming to enrich their ecosystem. 

Highlights

90% accuracy

Advanced HRMS Chatbot

Zero Human Intervention

Achieved workflow automation

Multilingual Chatbot Integration

Amazon Translate

The Challenge

The client faced challenges in HR operations due to manual workflows, decentralized data, limited support hours, and shift-based work. These challenges caused delays and customer dissatisfaction. With repetitive tasks draining resources, they sought CloudThat for an autonomous solution. 

“Thank you, Rishab I appreciate the support, professionalism, and timeliness shown by the CloudThat team Thank you, Arihant, Aditya, Arslan, and Saurabh.”

Vineeth Vijayan, Abright Labs

Solutions

  • The Natural Text-based HR Chatbot’s structured architecture ensures robust functionality, scalability, and seamless integration. 
  • An Amazon S3 bucket serves as a data lake for efficient storage of raw documents (PDFs, Docs), enhancing data management. 
  • Amazon Bedrock simplifies knowledge base management by handling data from Amazon S3 and selecting embedding models, streamlining workflow and query handling. 
  • AWS Lambda functions integrated with Amazon API Gateway and Amazon Bedrock enable seamless interaction with the chatbot from the front end. 
  • Integration with Amazon Comprehend enhances language processing capabilities by identifying input query languages (Spanish or English). 
  • Amazon Translate parses input queries to Amazon Bedrock, ensuring compatibility and accuracy in understanding user inputs. 
  • A separate AWS IAM user for developers in the delivery group ensures effective access and permissions management. 
  • Implementation of Amazon CloudWatch for comprehensive monitoring ensures system health and performance optimization. 

The Results

Developed a scalable HRMS chatbot on Amazon Bedrock, which enabled workflow automation and bilingual support with over 90% accuracy, enhancing HR operations and user experience. 

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