Kebotix utilizes a self-driving lab that integrates cloud technologies, machine learning, and physical modeling to accelerate materials discovery and production. This approach addresses the lengthy and inefficient R&D processes in material innovation, enabling faster market entry for new products.
Funding
$23.7M 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.
Founders
Product
Problem
Traditional materials science research and development is a slow, capital and labor intensive process, often taking many years to bring new materials to market. The trial-and-error nature of conventional lab work and reliance on human intuition limits the speed and efficiency of materials discovery.
Solution
Kebotix offers an AI-powered "self-driving lab" that accelerates the discovery and development of novel materials. By integrating cloud computing, machine learning, physical modeling, and robotic automation, Kebotix creates a closed-loop system where each iteration of material design, production, and testing informs the next. This approach enables faster exploration of the chemical space, optimized material properties, and reduced time-to-market for new products. The platform provides enterprise AI solutions customized for specific materials discovery needs.
Target Audience
The primary customers are companies in the materials science industry, including chemical, pharmaceutical, and manufacturing companies, seeking to accelerate their R&D processes and discover novel materials with improved properties.
Features
- Cloud-based platform integrating AI, physical modeling, and automation for materials R&D
- Closed-loop design paradigm enabling automated learning from each predict-produce-prove cycle
- Machine learning algorithms for predicting material properties and optimizing experimental design
- Robotic automation for high-throughput synthesis and characterization of materials
- Enterprise AI solutions customized for specific materials discovery applications