Brand-Safe Advertising Platform

Our Advertising Platform was a fully operational system with Facebook integration that allowed for the creation of advertising campaigns.


About the Client

Our client is a company with offices in London, New York, and Sydney. It delivers an AI-based advertising platform trusted by leading brands and agencies across the world. Our client maximizes the value of video advertising efforts YouTube, Amazon, Facebook & Instagram. Their platform is one of the most audited digital platforms, accredited by such prominent organisations as COPPA KidSafe, ABC, JicWebs Standards, IAB Gold Standard, etc.

Technologies Used


The client wanted to develop a prototype platform that allowed to create advertising campaigns and manage Facebook block-lists. They wanted to get an approval to use Facebook API. To do so they needed a properly developed MVP with basic functionality. Another task was to move their existing YouTube service from PHP to Java and implement a number of new features.

Work Description

First, Geomotiv conducted BA and developed an MVP prototype based on the accumulated data. After that, we sent the MVP to Facebook in order to get two approvals that would allow us to use the full Facebook API functionality. The cooperation went so well that the client wanted to continue it and set other tasks while the prototype was pending. One of them was to move their YouTube service from PHP to Java and implement integration in three main services, such as Amazon SageMaker comprising three Machine Learning models, Amazon Comprehend, and a client’s custom search service. We utilised the Natural Language Processing to perform that task.

Work Stages

  1. MVP design
  2. Backend development and other tasks
  3. Code review
  4. Deployment and DevOps
  5. End-to-end QA automation


The pilot project resulted in a long-term partnership. Facebook approved the delivered MVP, which enabled us to further proceed with the project. Apart from that, successful Java migration and service integration allowed the client to improve their system functionality.


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