case study

Bioscience Cloud-based Big Data Processing App Development


  • ML & AI
  • Frontend

Bioscience Cloud-based Big Data Processing App Development


NDA Protected

  • image Germany
  • image 5-10 employees

The client is a targeted proteomics company providing research services and discovering novel biomarkers especially around sports and personal well-being using state of the art proteomics methods.

request background

Collaboration journey

Initially, we were asked to create a graphical interface for developed back-end. Later, our Research and Development department worked on processing and analysis of biomaterials via AI & ML integration, and consulted on back-end optimization.


Fighting challenges

Our team was faced with a number of obstacles, holding us back from fast solution delivery. We had a rather restricted communication with an external back-end developer and his low engagement. Moreover, we had to find a way out of the low stakeholder engagement on the UAT step of a task workflow, which led to chaotic testing and constant iterations.


  1. AI & ML integration
  2. Back-end optimization
  3. Optimize analysis processing


Our working path

  • image ReactJS, Python, NodeJS, AWS
  • image 1+ years
  • image 3 specialists

We decided to organize the whole big data processing app development process in accordance with Scrum methodology, which created a single approach for task lifecycle management. Daily stand-ups gave us smooth communication between team members and external back-end developers, while periodic demos gave our clients understanding of the stage of the project and ability to suggest changes in product priorities more effectively.


No obstacles can stop us

  • Reduced the project time to launch by 30 percent
  • Increase in the analysis processing accuracy by 40 percent
  • Analysis processing time reduced by 38 percent
  • 30% Reduced the project time to launch
  • 40% Increase in the analysis processing accuracy
  • 38% Analysis processing time reduced

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