ExoMatter

About ExoMatter

ExoMatter is an AI-driven platform that streamlines materials research and development by providing access to a vast database of scientific materials data, enabling users to efficiently filter and rank materials based on specific criteria. This approach reduces the time and costs associated with traditional trial-and-error methods in materials R&D, allowing researchers to focus on the most promising candidates.

<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. </problem> <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. </solution> <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 </features> <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. </target_audience>

What does ExoMatter do?

ExoMatter is an AI-driven platform that streamlines materials research and development by providing access to a vast database of scientific materials data, enabling users to efficiently filter and rank materials based on specific criteria. This approach reduces the time and costs associated with traditional trial-and-error methods in materials R&D, allowing researchers to focus on the most promising candidates.

Where is ExoMatter located?

ExoMatter is based in Munich, Germany.

When was ExoMatter founded?

ExoMatter was founded in 2022.

How much funding has ExoMatter raised?

ExoMatter has raised 1800000.

Who founded ExoMatter?

ExoMatter was founded by Leonie Meyer and Josua Vieten.

  • Leonie Meyer - Founder of myuterus
  • Josua Vieten - Co-Founder/CEO
Location
Munich, Germany
Founded
2022
Funding
1800000
Employees
18 employees
Major Investors
Vanagon Ventures
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ExoMatter

Score: 100/100
AI-Generated Company Overview (experimental) – could contain errors

Executive Summary

ExoMatter is an AI-driven platform that streamlines materials research and development by providing access to a vast database of scientific materials data, enabling users to efficiently filter and rank materials based on specific criteria. This approach reduces the time and costs associated with traditional trial-and-error methods in materials R&D, allowing researchers to focus on the most promising candidates.

exomatter.ai1K+
cb
Crunchbase
Founded 2022Munich, Germany

Funding

$

Estimated Funding

$1.8M+

Major Investors

Vanagon Ventures

Team (15+)

Leonie Meyer

Founder of myuterus

Josua Vieten

Co-Founder/CEO

Company Description

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.

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

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.