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Chemix

Teserac provides safety, observability, and automation solutions specifically designed for AI infrastructure. The platform enables users to gain comprehensive visibility into their systems, understand operational status, and execute immediate actions. This integrated approach ensures reliable and efficient management of complex machine learning environments.

San Francisco, United StatesFounded 2021265K+ followers
Updated 20 months ago

Funding

$30.7M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.

Funding rounds are not available yet.

Founders

Product

Problem

The traditional process of designing electric vehicle (EV) batteries is slow, manual, and resource-intensive, creating a bottleneck in the development of next-generation batteries. This lengthy process also hinders the discovery of more sustainable battery chemistries that reduce reliance on critical and controversially sourced materials.

Solution

Chemix offers a GenAI-powered platform, MIX™, that accelerates the design and development of EV batteries. By leveraging a massive proprietary dataset and advanced machine learning algorithms, the MIX™ platform predicts material performance and optimizes battery designs, significantly reducing development time. The platform facilitates the discovery of novel battery chemistries that minimize or eliminate the need for cobalt, nickel, and lithium. Chemix's approach enables seamless integration with existing lithium-ion manufacturing processes, allowing for a faster transition from R&D to mass production of more sustainable and high-performance EV batteries.

Target Audience

The primary target audience includes electric vehicle manufacturers seeking to accelerate battery development, improve battery performance, and reduce reliance on critical materials, as well as e-motorbike companies and other EV companies.

Features

  • AI-driven material discovery engine to predict the performance of novel battery materials
  • Machine learning models to accelerate battery testing and predict battery longevity
  • Automated battery pilot facility for physical testing of different battery chemistries
  • Proprietary battery chemistries, including SAPPHIRE (low-cobalt) and JADE (cobalt- and nickel-free)
  • Designs compatible with existing lithium-ion battery manufacturing processes
This profile is AI-generated and may contain inaccuracies.