Enthought, Inc.

05/21/2026

In our recent presentation, From PoC to Production: Bridging the Gap in Scientific Software Development, Benjamin Luginbuhl walked through the path from proof-of-concept to production, and covered what a successful prototyping phase actually looks like.

The prototype phase should be scientist-led, AI-assisted, and fast. You're organizing and labeling key data, iterating quickly, and starting to think about whether agentic AI makes sense for your multi-step workflows.

But the part most teams miss is planning for all the phases from the start. Scaling is about 80% of the work. If you only budget for the prototype, you're planning for pilot purgatory.

Catch the full talk here: https://www.enthought.com/video-from-proof-of-concept-to-production

04/28/2026

Getting an AI prototype to work is hard. Getting it to production is harder.

On May 7, Benjamin Luginbuhl, PhD premieres his featured ACS Spring 2026 talk on Youtube: From Proof-of-Concept to Production: Bridging the Gap in Scientific Software Development.

What Ben walks through:
1. Where AI and materials informatics actually stand in R&D today
2. Why PoCs stall
3. A five-phase scaling playbook
4. What individuals, managers, and R&D organizations should each be doing differently

Register Now: https://www.enthought.com/video-from-proof-of-concept-to-production

Join Enthought expert for insights on transforming AI-driven prototypes into sustainable scientific software, addressing R&D challenges and bridging the gap to production-ready systems.

03/19/2026

The Inverted R&D Process

03/17/2026

Traditional materials R&D relies on trial and error experiments. Materials by Design (MbD) changes the process by starting with target performance and designing materials to achieve it using modeling and simulation. See how this approach is transforming materials discovery.

01/19/2026

Materials by Design is moving from theory to practice but only if the technical foundation is right.

On February 25th, Enthought is hosting a live webinar with C&EN: “A Technical Framework for Materials by Design in Enterprise R&D.” We’ll explore how advances in scientific AI and machine learning are making Materials by Design achievable for real-world, industry-scale R&D.

If you’re leading or supporting materials and chemistry R&D, and thinking seriously about how AI fits into your technical strategy, this conversation is for you.

➡️ Full details and registration: https://connect.discoveracs.org/Enthought_materialsbydesign

Can’t attend live? No worries, we will send the recording to all registrants.

01/08/2026

R&D doesn’t fail because teams lack ideas. It fails because too much time and money are spent validating the wrong ones. As generative AI floods R&D pipelines with possibilities, the real competitive advantage comes from knowing which paths not to pursue.

In this Forbes Technology Council article, Enthought COO Michael Connell explains why predictive AI is key to driving ROI in scientific R&D.

Read the full article here: https://www.forbes.com/councils/forbestechcouncil/2026/01/05/how-predictive-ai-works-as-an-roi-engine-for-rd/

True ROI for R&D won't come from the tool that generates 10,000 new ideas. It will come from the tool that confidently tells you which 9,990 to ignore.

11/12/2025

Agentic AI should be part of of every R&D leader's AI strategy, but change management is often the critical missing piece for ROI. Enthought's Michael Connell shares his perspective with CIO Online on how to prepare the workforce for an AI era: https://www.cio.com/article/4082282/preparing-your-workforce-for-ai-agents-a-change-management-guide.html

"𝘛𝘩𝘦 𝘣𝘦𝘴𝘵 𝘵𝘦𝘤𝘩𝘯𝘰𝘭𝘰𝘨𝘺 𝘥𝘦𝘭𝘪𝘷𝘦𝘳𝘴 𝘻𝘦𝘳𝘰 𝘷𝘢𝘭𝘶𝘦 𝘪𝘧 𝘯𝘰 𝘰𝘯𝘦 𝘶𝘴𝘦𝘴 𝘪𝘵, 𝘢𝘯𝘥 𝘢𝘥𝘰𝘱𝘵𝘪𝘰𝘯 𝘪𝘴 𝘵𝘩𝘦 𝘧𝘪𝘯𝘢𝘭, 𝘤𝘳𝘪𝘵𝘪𝘤𝘢𝘭 𝘮𝘪𝘭𝘦. 𝘓𝘦𝘢𝘥𝘦𝘳𝘴 𝘮𝘶𝘴𝘵 𝘯𝘰𝘵 𝘰𝘯𝘭𝘺 𝘣𝘶𝘥𝘨𝘦𝘵 𝘧𝘰𝘳 𝘤𝘩𝘢𝘯𝘨𝘦 𝘮𝘢𝘯𝘢𝘨𝘦𝘮𝘦𝘯𝘵 𝘢𝘴 𝘴𝘦𝘳𝘪𝘰𝘶𝘴𝘭𝘺 𝘢𝘴 𝘵𝘩𝘦𝘺 𝘣𝘶𝘥𝘨𝘦𝘵 𝘧𝘰𝘳 𝘣𝘶𝘪𝘭𝘥𝘪𝘯𝘨, 𝘣𝘶𝘵 𝘢𝘭𝘴𝘰 𝘪𝘯𝘷𝘰𝘭𝘷𝘦 𝘦𝘯𝘥 𝘶𝘴𝘦𝘳𝘴 𝘸𝘩𝘰 𝘢𝘳𝘦 𝘨𝘰𝘪𝘯𝘨 𝘵𝘰 𝘣𝘦 𝘵𝘩𝘦 𝘤𝘰𝘯𝘴𝘶𝘮𝘦𝘳𝘴 𝘰𝘧 𝘵𝘩𝘦 𝘵𝘦𝘤𝘩𝘯𝘰𝘭𝘰𝘨𝘺 𝘦𝘢𝘳𝘭𝘺 𝘢𝘯𝘥 𝘤𝘰𝘯𝘴𝘪𝘴𝘵𝘦𝘯𝘵𝘭𝘺 𝘪𝘯 𝘢𝘯 𝘢𝘨𝘪𝘭𝘦 𝘥𝘦𝘷𝘦𝘭𝘰𝘱𝘮𝘦𝘯𝘵 𝘱𝘳𝘰𝘤𝘦𝘴𝘴.
--- Michael Connell, COO, Enthought

Change management practices tailored to specific employee segments must be introduced early if your agentic AI strategy is going to deliver any positive business impact.

09/23/2025

In our latest webinar, Michael Connell breaks down the essential framework for implementing agentic AI in materials chemistry. Here's the key insight: success isn't just about the technology.

💡 "𝘞𝘩𝘦𝘯 𝘺𝘰𝘶'𝘳𝘦 𝘵𝘢𝘭𝘬𝘪𝘯𝘨 𝘢𝘣𝘰𝘶𝘵 𝘢 𝘣𝘶𝘴𝘪𝘯𝘦𝘴𝘴 𝘴𝘰𝘭𝘶𝘵𝘪𝘰𝘯, 𝘺𝘰𝘶'𝘳𝘦 𝘵𝘢𝘭𝘬𝘪𝘯𝘨 𝘢𝘣𝘰𝘶𝘵 𝘢 𝘴𝘰𝘤𝘪𝘰-𝘵𝘦𝘤𝘩𝘯𝘪𝘤𝘢𝘭 𝘴𝘺𝘴𝘵𝘦𝘮. 𝘐𝘵 𝘩𝘢𝘴 𝘵𝘦𝘤𝘩𝘯𝘰𝘭𝘰𝘨𝘺, 𝘣𝘶𝘵 𝘪𝘵 𝘢𝘭𝘴𝘰 𝘩𝘢𝘴 𝘱𝘳𝘰𝘤𝘦𝘴𝘴 𝘢𝘯𝘥 𝘩𝘶𝘮𝘢𝘯 𝘣𝘦𝘪𝘯𝘨𝘴."

This layered approach forms what we've found to be the "minimum viable toolkit" for successful agentic AI initiatives in materials science.

Watch the full discussion: https://www.enthought.com/webinar-agentic-ai-in-materials-chemistry-2025

09/16/2025

R&D leaders today face an ever-growing challenge: Which technical projects should we prioritize in the lab?

There are usually too many promising ideas competing for too few resources. Without a clear framework, R&D orgs risk wasting limited budgets, missing opportunities, and stalling innovation.

In new Forbes Technology Council article, Enthought's Michael Connell explores how a strategic roadmap avoids the costly trap of “everything is a priority” and introduces his Three-Swimlane Framework to help R&D leaders prioritize technical projects with clarity.

Read more 👉https://www.forbes.com/councils/forbestechcouncil/2025/09/12/the-magic-of-a-roadmap-how-to-prioritize-technical-projects-in-rd/

Fear of competitors leveraging AI successfully, coupled with significant investments required in talent, infrastructure and data governance, increases pressure to choose wisely.

09/05/2025

🤖 Agentic AI is disrupting materials and chemistry R&D, but it's easy to get lost in the jargon and hype. Join us for the upcoming webinar "Making Sense of Agentic AI: A Strategic Briefing for Materials & Chemistry R&D Leaders."

Enthought's experts will demystify agentic AI—what it is, why it matters now, and how to think strategically about adoption, impact, and long-term value in materials and chemistry R&D. This isn't another technical deep dive—it's a strategic conversation for leaders on why agentic AI is a game-changer for R&D organizations with practical guidance on how to get started.

➡️ Full details and registration link: https://events.enthought.com/agentic-ai-in-materials-chemistry-2025

Bonus! Registrants will receive a curated list of R&D-relevant resources on agentic AI after the event.

Can’t attend live? No worries, we will send the recording to all registrants.

08/13/2025

The shift from sequential to concurrent materials design is transforming R&D. In our latest blog, we explore how three critical AI capabilities are enabling this leap: advanced optimization, generative AI, and agentic AI systems.

Companies like Dow, 3M, Apple, and Tesla are already leveraging this approach to co-optimize materials alongside product design, processing conditions, and manufacturing from the initial concept phase, achieving faster development cycles and globally optimized solutions.

This isn't gradual change. It's a fundamental paradigm shift that allows R&D teams to create superior, differentiated products.

https://www.enthought.com/blog/concurrent-materials-design-accelerated-by-ai/