• Reuse the existing code logic  
• Map the complicated calculation logic from the existing app to the new app 
• Retain all features yet give it a better User experience  

•  Landing Zone Drift
• Role Drift
• Security Hub Control Drift
• Trusted Access disabled

• Collate all accounts together 
• Understand and agree on how the account would be managed under the distribution model  

• Integrated Patient Profile with NDHM: This application seamlessly integrates with NDHM, enabling the swift creation of ABHA IDs and facilitating the exchange of patient health data. By interfacing with the National Digital Health Mission, the system ensures that patient data is standardized, up-to-date, and easily accessible, fostering more informed medical decisions.
• Multi-tenancy Architecture: The system’s ability to cater to multiple hospitals or health providers under a single unified platform is a significant advantage. Each hospital can manage its operations while benefiting from centralized updates and features, ensuring scalability and simplifying administrative tasks.
• Data Encryption at Rest and In Transit: Implemented encryption using AWS Key Management Service (KMS) for both data at rest (S3, EBS, RDS) and in transit (SSL/TLS) to ensure compliance with GDPR and HIPAA requirements for securing sensitive data.
• Identity and Access Management (IAM): Designed and enforced strict least-privilege access policies using AWS IAM. This included creating custom roles and policies with granular permissions for specific users and services, ensuring only authorized personnel had access to sensitive data.
• AWS Config and Compliance Rules: Set up AWS Config to track and audit configuration changes across the environment. Applied AWS Config Rules to continuously monitor compliance against GDPR and HIPAA requirements, such as encryption enabled on S3 buckets and logging for API Gateway and Lambda.
• Audit Logging and Monitoring: Configured AWS CloudTrail and Amazon CloudWatch for continuous logging and monitoring of API calls, changes, and actions within the AWS environment. This was crucial for meeting HIPAA requirements for audit trails and GDPR’s data access visibility.
• VPC Flow Logs and Security Groups: Deployed Virtual Private Cloud (VPC) with properly configured flow logs to monitor and log network traffic. Used AWS Security Groups and Network ACLs to ensure secure network segmentation and prevent unauthorized access to sensitive resources.
• Data Residency and Data Transfer Controls: Implemented controls to ensure data residency compliance by restricting data storage and processing to specific AWS regions as required by GDPR. Utilized VPC endpoints and AWS Direct Connect to secure data transfers and reduce the exposure to the public internet.
• Backup and Disaster Recovery: Designed an automated backup strategy using AWS Backup to meet GDPR’s requirement for data recoverability, ensuring regular snapshots of critical databases (e.g., RDS, DynamoDB) and storing them in encrypted S3 buckets across different regions for redundancy.

We encountered some ssues as below: 

• Establishing a pre-defined system criterion which needs to be met before uploading the picture. This includes deciding threshold value for the image processing algorithms to be implemented for removal of white spaces present on the side of ID card and skewness present in the image captured
• The Canny algorithm used for border detection had some limitations and didn’t work in all the scenarios where ID card had more prominent rectangle drawn on it or an image with white background of a white ID card. These cases didn’t gave a correct collection of lines and may have resulted in incorrect border detection. To overcome this problem we implemented FindContours on binary image which gave us a more reliable result
• We had to cater for devices of varying power and capability since this solution implementation had to run on various platforms. As we got into the testing phase we had to avoid large variation in responsiveness depending on the device used

• Access was not provided to the actual environment and setting up 
• Complex environment setup and monitoring for production cost was only possible to evaluate if we have got the access for the actual environment from the client

• Logging in to have the same user access the store front and mobile to have one seamless experience on any device
  • We used Auth0 and Shopify APIs to authenticate the same user if it exists already on Shopify web app
• Initially we hardcoded the logic for categories on the mobile side but that would mean frequent code update and if the client needs to change something on the product or category had to come back to the development team 
  • Integrated with the shopify store to ensure that categories and product information is read from the backend and not hard coding any logic on the app side 
• Mobile App should behave same as the Shopify store front and there were some data validation logic like Coupon code, Pin code validation etc which were not working as expected
  • We integrated the same logic using APIs for all data validation hence the app behaved exactly like the web store front.  

• After our 2 successful implementations we were mostly in control of how the app would work and the rollout process. However, there were some UI fixes and a new charting capability which was required to help make the reporting section of the app more user-friendly. We had a charting 3rd party component already implemented which did not suffice the requirement from the client side 

• A new custom charting component was implemented to deliver as per client’s requirement.
• Making the app work similar for the existing deployed solution in other groups as well.
• We deployed the same build with the new features rolled out for other Pioneer Group companies using the same app.