Our first product is an end-to-end solution to maximize the value of lithium-ion assets using machine learning. Our unique machine learning solution empowers the owners of Commercial EVs 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.
Sensai Lithium
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
Team
Muhammad Rizwan
ML Research Scientist
Georgia Tech Ph.D.
Ian Mathews
CEO | Co-Founder
Erin Looney
Co-Founder
MIT Ph.D.
Advisors
Prof. Bolun Xu
Columbia University
Bruce Lawler
Director | MIT Machine Intelligence for Manufacturing & Operations
Paul King
Battery Scientist
Trinity College Dublin Ph.D.
Request a Demo
Schedule a demo with one of our team.