Digital transformation is revolutionizing
scientific innovation.
Enthought solves complex data challenges for enterprise scientific R&D labs.
We develop custom machine learning and AI-driven data tools and applications that accelerate scientific discovery.
We deliver holistic solutions that create cost efficiencies and uncover new revenue opportunities for the business.
We build the digital capabilities of the scientific workforce to foster continuous innovation and strengthen competitive advantage.
Our Insights
Understanding Surrogate Models in Scientific R&D
Surrogate models are reshaping R&D by making research faster, more cost-effective, and more sustainable.
R&D Innovation in 2025
As we step into 2025, R&D organizations are bracing for another year of rapid-pace, transformative shifts.
Revolutionizing Materials R&D with “AI Supermodels”
Learn how AI Supermodels are allowing for faster, more accurate predictions with far fewer data points.
What to Look for in a Technology Partner for R&D
In today’s competitive R&D landscape, selecting the right technology partner is one of the most critical decisions your organization can make.
Digital Transformation vs. Digital Enhancement: A Starting Decision Framework for Technology Initiatives in R&D
Leveraging advanced technology like generative AI through digital transformation (not digital enhancement) is how to get the biggest returns in scientific R&D.
Digital Transformation in Practice
There is much more to digital transformation than technology, and a holistic strategy is crucial for the journey.
Leveraging AI for More Efficient Research in BioPharma
In the rapidly-evolving landscape of drug discovery and development, traditional approaches to R&D in biopharma are no longer sufficient. Artificial intelligence (AI) continues to be a game-changer.
Utilizing LLMs Today in Industrial Materials and Chemical R&D
Leveraging large language models (LLMs) in materials science and chemical R&D isn’t just a speculative venture for some AI future. There are two primary use cases that are ready for adoption in research labs today.
Top 10 AI Concepts Every Scientific R&D Leader Should Know
R&D leaders and scientists need a working understanding of key AI concepts so they can more effectively develop future-forward data strategies and lead the charge towards groundbreaking discoveries.
Why A Data Fabric is Essential for Modern R&D
Scattered and siloed data is one of the top challenges slowing down scientific discovery and innovation today. What every R&D organization needs is a data fabric as part of their technology solution set.
Compute-Centric R&D
Enthought aims to answer the question “what could be accomplished if our scientists could spend 100% of their time advancing their discoveries?” By applying advanced computing techniques and systems, we transform R&D data challenges into data opportunities. From idea generation and technical implementation to extracting business value, we deliver a digital transformation that will impact the entire business ecosystem.
Purpose-Built for Science
Enthought has extensive experience in leveraging technology to transform how science is conducted in industry. Our powerful solutions are grounded in a deep understanding of the complexities of scientific data and the most advanced machine learning and AI techniques. We empower scientists by turning their data into analysis-ready assets for solving today’s problems and producing tomorrow’s innovations.