Zenda: A platform to manage medical expenses

Zenda is a platform that helps employees categorize and track medical expenses for enhanced payment management. It allows corporate employees to track medical costs, manage payments, and save money. Zenda ia a leading financial management platform for employees in an organization to track all the transactions, and manage payments. 

• Zenda faced intricate challenges in handling vast financial datasets submitted by clients.
• Need for validation of the data shared by employees against the business logic, added to the complexity of handling financial datasets
• Ensuring a scalable and secure Know Your Customer (KYC) process was crucial for regulatory compliance.
• The secure generation of financial accounts post-KYC required a streamlined mechanism.
• Automation of data tasks, reducing latency, and enhancing system scalability were paramount in meeting dynamic financial demands.

• Simform helped Zenda create a mechanism that can process large data files using a serverless approach.
• Our experts leveraged AWS Lambda to facilitate efficient data extraction and transformation.
• We implemented AWS CloudFormation to create a scalable infrastructure for large data files.
• Our team also leveraged AWS Lambda to implement the business logic validation for user data using a serverless function,
• We implemented Amazon API Gateway to handle API requests and route the KYC request to the appropriate Lambda function to apply business logic. 
• To facilitate seamless transactions, we created a containerized environment leveraging Amazon ECS.
• After applying the business logic, our AWS experts used Amazon DynamoDB to store validation results.
• Our team used Amazon Eventbridge to automate, trigger, monitor, and analyze events in the system. 
• We deployed Amazon SES to send emails to the users for bank account creation.
• We handled the data task queues using Amazon SQS and leveraged AWS SNS to notify API Gateway if a new data task was added. 
• Our team used AWS Cognito to manage user identities and data privileges
• We also deployed AWS Lambda to automate back account creation for each user and used Amazon EC2 to create a scalable environment for multiple bank account generation.
• Our team monitored the entire process using Amazon CloudWatch. 
• We implemented AWS CloudFormation to create a scalable infrastructure to facilitate seamless operations.
• We also used Amazon RDS as a central repository to store and process large data files shared by users and Amazon S3 for long-term storage of large files. 

• Maintain a 99.9% system uptime for the AWS RDS PostgreSQL database to ensure continuous availability of financial data.
• Demonstrate a 70% reduction in data processing time through efficient data extraction and transformation using AWS Lambda.
• Utilize Amazon API Gateway for routing KYC requests to Lambda functions, achieving a 65% efficiency improvement in the KYC process.
• Ensure 100% accuracy and compliance with regulatory standards in financial data processing.
• Achieve zero errors in data validation against business logic to meet strict regulatory requirements.

• AWS Lambda: We used AWS Lambda to facilitate low-latency data extractions and implement business logic validations for the KYC process.
• AWS CloudFormation: Our team created a scalable infrastructure to store large data files leveraging AWS CloudFormation
• Amazon API Gateway: We used Amazon API Gateway to handle API requests and ensure each request is routed to the appropriate AWS Lambda function.
• Amazon DynamoDB: Our experts used Amazon DynamoDB to store the KYC results after implementing the business logic validations.
• Amazon SES: We used Amazon SES to send email notifications to the users for bank account generation
• AWS Cognito: Our team used AWS Cognito to define data privileges and manage user identities to ensure data security.
• Amazon RDS: We used Amazon RDS as a central repository for the systems to store large data files. 
• Amazon SQS: Our team used Amazon SQS to handle leveraged AWS SNS to notify API Gateway if a new data task was added
• Amazon Eventbridge: Our team used Amazon Eventbridge to automate, trigger, monitor, and analyze events in the system. 
• Amazon EC2: Our team used Amazon EC2 to create a scalable environment for multiple bank account generation
• Amazon ECS: We created a containerized environment leveraging Amazon ECS for the transaction process