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Deep Forest Sciences

This company develops Prithvi, an AI assistant powered by Scientific Foundation Models to accelerate discovery in drug development and materials science. It leverages DeepChem infrastructure to provide modular AI that blends human intuition with machine intelligence for molecular design. The platform enables faster breakthroughs across various scientific domains with minimal data requirements.

Fremont, United StatesFounded 202113700+ followers
Updated 20 months ago

Funding

Funding not disclosed

HE
Funding rounds are not available yet.

Founders

Founder details are not available yet.

Product

Problem

Drug discovery, energy solutions, and molecular design are often slowed by the need for extensive datasets and the difficulty in identifying promising molecules and materials. Traditional methods struggle to efficiently navigate the vast chemical space and predict the properties of novel compounds.

Solution

Deep Forest Sciences offers Prithvi, an AI assistant that leverages Large Scientific Foundation Models to accelerate scientific discovery in medicine, energy, and materials science. Prithvi reduces the data requirements for effective molecule and material identification by blending human intuition with machine intelligence. The platform utilizes the DeepChem framework to provide a modular AI solution that can be deployed across various projects. By harnessing scientific foundation models and cutting-edge AI techniques on proprietary data, Prithvi accelerates the discovery process and enables faster breakthroughs.

Target Audience

The primary target audience includes researchers and scientists in the fields of drug discovery, energy, and molecular design who seek to accelerate their research and development processes using AI-driven insights.

Features

  • AI assistant powered by Large Scientific Foundation Models
  • Leverages the DeepChem framework for modular AI development
  • No-code fine-tuning capabilities for chemical foundation models
  • No-code relative binding free energy (RBFE) calculations
  • No-code molecular dynamics simulations
  • No-code DEL-ML (DNA-Encoded Library Machine Learning) analysis
  • No-code molecular docking
This profile is AI-generated and may contain inaccuracies.