How we helped the customer build a personal information scrambler


The client, a prominent European bank currently undergoing a digital transformation, encountered a scenario wherein they required a solution to track the customer journey for each user without relying on any personally identifiable (PI) data for analytical purposes.

GESHDO proposed a solution that was deemed suitable, leading to their involvement in the implementation of the idea.

Drawing upon extensive industry expertise and leveraging the capabilities of cloud technology, GESHDO swiftly developed and deployed the initial version within a mere two-week timeframe.

Our solution collected the PI data necessary for tracking the user's customer journey. This data was then sent to our server, where it was promptly salted and hashed. Subsequently, a random GUID (Globally Unique Identifier) was generated, and the resulting hash and GUID were stored in a database. The GUID was then returned to the customer application, enabling the use of the GUID in place of the PI data.

This approach ensured that no PI data was utilized for analytical purposes, providing each user with a unique, non-identifiable, and consistent identifier. Retrieving the same identifier was only possible by requesting our service with the same PI data.

GESHDO built the foundation and are now operating and maintaining the system while working in two weeks sprints to deliver new and exciting features.


We early on decided on three ground rules to follow through the whole project.

Time to market

To facilitate rapid testing of the concept, quick action was imperative. Consequently, the initial version, encompassing all fundamental features, was developed and deployed within a mere two-week period.



Given the sensitive nature of the data pertaining to the bank system, ensuring top-notch security was our primary concern. Leveraging our expertise and adhering to best practices, we successfully cleared the internal security audit without any remarks.


Respect the cost

No solution can be respected if you do not know the cost and this was something we continuously tracked during the project.


Here are three interesting metrics that symbolized our commitment to building cheap, reliable and fast solutions.


The cloud cost for running the solution each month.



Amount of downtime since launch.


2 weeks

Time to build the the initial MVP.


We used a array of multiple technologies in this project. Each carefully selected based on cost, performance and ease to use.


  • .Net Core
  • C#
  • SAM
  • Docker

Cloud Services

  • Amazon Web Service
  • API Gateway
  • Lamba
  • DynamoDB
  • Cloud Watch
  • Secrets Manager
  • Systems Manager
  • CloudFormation
  • Terraform