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Dr. Lal PathLabs is a leading publicly listed diagnostic chain with focus on providing patients quality diagnostic healthcare services in India. Learn more about them here.

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    Dr. Lal Pathlabs

     

    Enabling Dr. Lal PathLabs to Deliver an Omnichannel Experience with AWS Tech.

    About Dr LalPath Labs

    Dr. Lal PathLabs is a leading publicly listed diagnostic chain with focus on providing patients quality diagnostic healthcare services in India. Learn more about them here.

    THE CHALLENGE

    Dr. Lal PathLabs was running multiple systems with legacy technologies and rigid architectural design which became a roadblock for their digital transformation journey. With the current setup they were finding it difficult to scale their system, achieve operational efficiency and deliver an omni-channel experience to their customers. They were in need of a system which could be scalable, secure and reliable to handle their growing business.

    Dr. Lal Pathlabs

    SOLUTION OVERVIEW

    We built an end-to-end integrated ecosystem for their diagnostics operations, covering all the touchpoints. With this system, LPL is now able to control and monitor all its operations from a singular interface, including both consumer facing and operational apps for various personas. We have built a dashboard that generates in-depth reports and data insights on what's going on with the business while tracking KPIs.


    HOW [x]cube LABS LEVERAGED AWS TECH.

    [x]cube partnered with Dr. Lal Pathlabs and Amazon Web Services (AWS) was the technology of choice as it met all the requirements of building the solution.

    AWS CloudFront allows hosting Dr. Lal Pathlabs eCommerce, Home Collection, Patient Registration, Phlebotomist Tracking static websites. It provides a simple approach for storing and delivering static content using an Amazon S3 bucket. Using CloudFront, we took advantage of the AWS backbone network and CloudFront edge servers to design a fast, safe, and reliable experience for viewers when they visit the websites.

    We have deployed the application using AWS ECS (Elastic Container Service) as it allows the deployment of docker containerized microservices and Batch Jobs. The dynamic port mapping and path-based routing features of Elastic Load Balancing Application Load Balancers provide service discovery for a microservice architecture. It offers a great flexibility to scale the services up & down easily and also, supports autoscale services according to the load.

    Being a health service provider, API security is a key concern for which we have used AWS WAF services to protect web applications or APIs from common web exploits and bots that may affect availability, compromise security, or consume excessive resources.


    Dr. Lal Pathlabs
    Dr. Lal Pathlabs
    Dr. Lal Pathlabs
    Dr. Lal Pathlabs

    AWS RDS: We have used the MySQL Database engine. This service is used to handle multiple key features which are utilized throughout the system such as test slot booking, details on orders allocation, Phlebos & Admin users and also, the master data such as tests & its pricing details.

    With over 5000+ diagnostic tests accessible from multiple online channels, it’s critical to deliver search results effectively. We have used AWS ElasticSearch that does a great job with 100% matching criteria even though sometimes the search inputs are fuzzy.

    AWS Elasticache (Redis) is used to maintain the frequently used, yet rarely modified data so we can minimize the database calls and load.

    AWS SQS is used to process more requests with minimal time without losing the orders pushed to the queue with the threading concept. The orders which are received by the system are dynamically sent to another system where the actual processing takes place.

    AWS S3 is used to maintain the static data and dynamic data such as user profile pictures & invoices.

    BENEFITS

    • Reduction in support call ticket by 15%
    • Increase in test booking capacity
    • Improved information visibility and transparency
    • Improved lab capacity utilization


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