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ractangle
case study

Bioscience Cloud-based Big Data Processing App Development

Healthcare

  • ML & AI
  • Frontend

Bioscience Cloud-based Big Data Processing App Development

client

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.

client

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.

challenge

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.

goals

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

solution

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.

outcome

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
cta

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