Problem
Niche Vision's analysts were tasked with manually analyzing blood sample diversification from multiple sources, which was both time-consuming and prone to human error. The process involved interpreting complex diagrams and estimating how many individuals were represented in a given sample. This led to inconsistencies in data interpretation and hindered the efficiency of medical research and diagnostic applications.Additionally, as the volume of blood sample data increased, the existing workflow became unsustainable. Analysts faced bottlenecks in processing large datasets, limiting their ability to deliver timely and accurate insights to healthcare institutions. The company needed a scalable, automated solution to enhance prediction accuracy and streamline its research workflows.
Solution
Niche Vision partnered with Zams to implement a custom AI model that utilizes a chain of binary classification models. By leveraging Zams' predictive AI capabilities, the model processes columnar datasets and delivers precise estimations of how many individuals are represented within a given sample.This AI-driven approach replaced the manual review process with an automated prediction system, significantly reducing analyst workload and improving accuracy. The model's ability to consistently interpret and classify blood sample data enabled Niche Vision to scale its operations efficiently while maintaining high standards of reliability in its research findings.
Outcome
With the AI model powered by Zams, Niche Vision saw a 45% increase in sample prediction accuracy, reducing inconsistencies and improving overall data reliability. The automation of the analysis process allowed the company to cut manual review time by 60%, freeing analysts to focus on higher-level research and strategy.The enhanced efficiency led to a 50% overall improvement in research workflows, enabling Niche Vision to support more healthcare institutions with faster and more precise diagnostic tools. This AI integration not only streamlined their operations but also positioned the company as a leader in bioinformatics-driven healthcare solutions.
