
METLiT, founded in 2021 by MRS experts, offers an AI-powered metabolic profiling solution that provides non-invasive, real-time biochemical snapshots of cellular activity using MR Spectroscopy (MRS). Their mission is to simplify MRS, making it more accessible and improving its fidelity in clinical fields by transforming conventional MRS, which typically requires specialized expertise. METLiT provides institution-customized AI-aided MRS solutions for various medical purposes. Their AI solution combines conventional methods with deep learning for quantification, reducing MRS scan and processing times. The product is a cloud-based SaaS solution compatible with major MRI scanners from GE, Philips, and Siemens, enabling automated analysis of metabolite information for diagnosis, treatment prognosis, and medical research. It offers precise analytic performance with deep-learning based quantification for up to 17 metabolites and an enhanced workflow with a 50% reduction in scan time and 95% reduction in analytic time.

METLiT, founded in 2021 by MRS experts, offers an AI-powered metabolic profiling solution that provides non-invasive, real-time biochemical snapshots of cellular activity using MR Spectroscopy (MRS). Their mission is to simplify MRS, making it more accessible and improving its fidelity in clinical fields by transforming conventional MRS, which typically requires specialized expertise. METLiT provides institution-customized AI-aided MRS solutions for various medical purposes. Their AI solution combines conventional methods with deep learning for quantification, reducing MRS scan and processing times. The product is a cloud-based SaaS solution compatible with major MRI scanners from GE, Philips, and Siemens, enabling automated analysis of metabolite information for diagnosis, treatment prognosis, and medical research. It offers precise analytic performance with deep-learning based quantification for up to 17 metabolites and an enhanced workflow with a 50% reduction in scan time and 95% reduction in analytic time.