Kebotix provides R&D solutions through enterprise AI customized for materials discovery, leveraging cloud technologies, machine learning, and automation.

Kebotix

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Chairman

Ashish Kulkarni

Chief Product Officer

Christoph Kreisbeck

Chief Technology Officer

Dennis Sheberla

Jill Becker

Vice President Business Development and Partnerships

Scott Healey

Director of Product Marketing

Holly McAlpine

Sr. Financial Controller

Denise Drinkwater

Machine Learning Chemist

Grit Kupgan

Lead Machine Learning Scientist

Sam Elder

Various

Selma Duhović

Jeff Bussgang

Alán Aspuru-Guzik

Chief Visionary Officer

Chief Executive Officer

Semion Saikin

Chief Science Officer

Founder & Chief Product Officer

Founder & Chief Technology Officer

Chemical Female Founded Companies

Greater Boston Area Companies (Top 10K)

Machine Learning Companies With Less Than $50M in Revenue

Harvard University Alumni Founded Companies

Kebotix is a high-tech materials discovery and production company. It is to reinvent the materials industry and enable a new age of discovery of new materials using AI, machine learning, and robotics.

It was founded in 2017 and is headquartered in Cambridge, Massachusetts.

Venture Round - Kebotix

Novo Holdings

Series A - Kebotix

One Way Ventures

Seed Round - Kebotix

Computer and Software Services and Scientific Services

Cambridge

Massachusetts

United States

North America

Pyrazole compounds for organic light emitting diodes and other applications

Predicting molecule properties using graph neural network

Emitting materials for electroluminescent devices and other applications

Organic colorants, including pigments and dyes, for plastics, inks, paints, …

Systems and methods for electrochromic molecules

Kebotix Tapped by EPA to Develop Safe Pigments

Kebotix, SCM Partner to Advance Materials Innovation

Kebotix on Cusp of 'Promising' OLED Breakthrough

A software platform that integrates lab instruments, coordinates workflows, and collects data in an AI-processable format to optimize chemical synthesis and process chemistry.

An AI-based tool that predicts novel and diverse sets of reaction pathways for forward and retro synthesis.

Tools that enhance modeling capabilities using deep learning and probabilistic machine learning to predict physical properties and reduce experimental testing of materials.

Algorithms designed to accelerate product development by making smarter experiments, saving time, and reducing costs.

A lab that combines cloud technologies, machine learning, physical modeling, and automation to optimize the R&D process.

Customized AI solutions for materials discovery to digitize R&D workflows and enhance productivity.

Brazil

South America

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news impact assignment basic	general
public peers	general	Oct 30, 2024 6:41 AM	ec5b9a11
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