• A major biotech research institute specialized in Proteomics, faced several challenges in  establishing an effective linkage between their data acquisition channels from experiments and the core customizable analytics engine. 

• MerSci developed a customized platform to automate and scale the analytics pipeline by real-time ingestion of the streamed data from experiments into the analytics engine.

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• It provides a vast set of insights through various analysis techniques ranging from statistical analyses such as feature interaction analysis, sequential data modeling, and design of experiments to machine learning-based solutions  such as anomaly detection and cluster analysis.                

• The developed solution played a major role in supporting basic and clinical research needs. It provided an integrated environment to perform  end-to-end development of various analyses on real-time streaming data.

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• Leveraging cutting-edge technologies such as GPU-accelerated analytics, the time for solution prototyping was reduced significantly which resulted in a substantial efficiency gain.