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LATEST NEWS

Enthought Appoints Toshio Mii as Chairman to Lead Next Chapter of AI-Driven Scientific Innovation in Japan

Agentic AI and the Future of Scientific R&D

SOLUTIONS

Software & AI
Scientific Software Development, Legacy Software Modernization, UI/UX,
Predictive Modeling, Custom Simulations, Web Applications,
Multimodal Knowledge Systems, API Development

Data Systems
Data Engineering, Process Engineering, Data Pipelining and Augmentation,
Workflow Automation and Redesign, Scientific Data Management Systems,
Data Capture Systems, High Volume Data Management, Database Design

Strategy & Design
R&D AI Transformation, R&D Digital Transformation, Strategic Roadmap Development,
Data System Design, Process Analysis

Infrastructure
Technical Upskilling for Scientists & Engineers, R&D Systems Integration,
R&D IT and Data Ops

INDUSTRIES

Materials Science & Chemistry
Semiconductors
Life Sciences
Energy

QUICK LINKS

Agentic AI
Materials by Design

TECHNOLOGIES

Core Technologies
Machine Learning, Deep Learning, Baysian Optimization, Generative
Adversarial Networks, Graph Neural Networks

Advanced Modeling & Systems
Reasoning Models, Multi-Scale Modeling, Surrogate Modeling,
Simulation, Image Processing, Agentic AI Systems

Language & Generative AI
Natural Language Processing, Foundation Models, Generative AI,
Large Language Models

USE CASES

Discovery & Development
Property Prediction, Formulation Optimization, Structure Generation,
Materials Discovery, Materials Compatibility

Data Insights
Text Data Mining, Automated Data Analysis, Time Series Analysis,
Multimodal Search, Literature and Patent Search, Dashboards, Data Visualizations

Decision Support
Chatbots, Predictive Maintenance, Preventative Maintenance, AI
Recommendation Systems

RESOURCES

A Technical Framework for Materials by Design | View the recording for this timely webinar on Materials by Design for enterprise R&D.

Industry Expertise

Life Sciences

With the race to develop novel therapies and the growing complexity of biologics, pharma and biotech R&D faces mounting pressure to accelerate discovery, streamline development, and deliver life-changing treatments to patients faster than ever.

AI-Driven Drug Discovery & Development

Traditionally, the process of developing new drugs has been complex, costly, and slow, with the average time of getting a new drug from discovery to market being 12+ years. Life sciences companies are now investing heavily in artificial intelligence—and for good reason. Pharmaceutical and biotech R&D labs that leverage AI and machine learning are accelerating discovery and getting to clinical trials faster. However, many companies today are still entrenched in traditional methods of scientific research. Enthought helps pharmaceutical companies and CROs of all sizes harness the power of AI to expedite drug discovery and development, all centered around their unique IP.

cell-culture

How Agentic AI Can Keep Your Best People’s Knowledge from Walking Out the Door

Every R&D organization has a version of the same problem: the people who know the most are often the closest to...

Why R&D AI Pilots Stall and How to Get Out of Pilot Purgatory

This content was originally discussed in the presentation, From PoC to Production: Bridging the Gap in Scientific...

The Capability Inflection Point: Agentic AI in Scientific R&D

Why Science, Why Now? The frontier AI companies have placed a coordinated bet on science. OpenAI launched...

Ready to Take the Next Step?

Whether you need to get your R&D organization AI-ready or are ready to capitalize on advanced AI, Enthought can help.