Our first product is an end-to-end platform to maximize the value of lithium-ion assets using machine learning. Our unique machine learning solution empowers clients to forecast the residual value of retiring EV batteries, enabling a battery circular economy and value-driven decision-making on whether to refurbish, reuse or recycle battery assets.
What is Data-Centric AI?
Building Data-Centric AI means developing end-to-end machine learning solutions that focus on data, not models. A shortage of Big Data, or difficulty using it, is restricting the majority of companies from creating massive value with AI. By developing methods that overcome sparse data challenges, smartly transfer data and knowledge across projects, and simplify model deployment and management, Sensai Analytics makes it easy for companies to use and scale AI across their electrification projects.
01. Faster model building
We've helped companies reduce the time to build AI solutions for their products and operations by 85%
02. Faster time to value
This leads to an almost 10x improvement in 'time-to-value' for AI projects
03. Increased productivity
And massively increases the productivity of in-house data science teams - a group currently over-stretched by the demand for solutions but shortage of talent available
ML Research Scientist
Georgia Tech Ph.D.
CEO | Co-Founder
Prof. Bolun Xu
Director | MIT Machine Intelligence for Manufacturing & Operations
Trinity College Dublin Ph.D.
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