ExoMatter provides an AI-powered platform for materials research and development, specializing in inorganic crystalline materials. The platform uses machine learning to screen materials based on performance, sustainability, and cost, accelerating discovery beyond traditional trial-and-error methods. This digital R&D approach helps scientists efficiently evaluate material alternatives for applications in sectors like batteries and semiconductors.
Funding
$1.8M 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.
VVFounders
Product
Problem
Materials research and development is traditionally a time-consuming and expensive process, relying heavily on trial-and-error methods. Researchers face challenges in efficiently accessing, filtering, and ranking the vast amounts of available materials data. This can lead to delays in discovering optimal materials for specific applications and increased R&D costs.
Solution
ExoMatter offers an AI-powered platform designed to streamline materials R&D by providing access to a comprehensive database of scientific materials data. The platform enables users to efficiently filter and rank materials based on specific criteria, leveraging AI tools and data-mining capabilities. By standardizing and enriching data, ExoMatter helps researchers focus on the most promising materials candidates, reducing the need for extensive trial-and-error experimentation. The platform supports both accessing global materials data and working with proprietary datasets in a secure cloud environment. This data-driven approach allows for quicker reactions to changing requirements, such as supply chain issues or new regulations.
Target Audience
ExoMatter primarily targets materials R&D teams in the chemical, manufacturing, and new energy sectors, as well as researchers in automotive and aerospace industries.
Features
- Access to a global database of millions of scientific materials, updated and easily searchable
- AI-powered tools for data enrichment and intelligent filtering of materials based on user-defined criteria
- Customizable dashboards for data visualization and collaboration across teams
- Secure cloud environment for working with proprietary and combined datasets
- Autonomous search functionality using multiple parallel search criteria
- Proprietary scoring and ranking system to curate a shortlist of optimal materials