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
Enthought, Inc.
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Accelerating Scientific Discovery with Purpose-Built AI Expertise in machine learning, AI, and IIoT.
Python software, consulting, training, and support for scientists, engineers, analysts, and data scientists.
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
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.
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