“I’d love to use data-driven optimisation, but I don’t have the coding skills.”

“I’d love to use data-driven optimisation, but I don’t have the coding skills.”

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I hear this all the time and I can relate as a chemist.

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Personally, I only found my way into coding relatively late.

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In my experience, the biggest AI barrier in chemistry isn’t the algorithm. It’s usability.

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That’s exactly what I spoke about at the @5-HT Chemistry & Health Innovators Club, focused on lab digitalisation and automation at the ZEISS Innovation Hub @ KIT.

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At @ReactWise, our mission is to put chemists at the centre of the AI shift - and give teams access to data-driven optimisation without writing a single line of code. 

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We make advanced optimisation practical for everyday process development by helping lab teams run fewer, more informative experiments instead of trial-and-error, while also answering the “why” behind results: why certain conditions are promising, which trends and interactions are hidden in the data, and how insights can be communicated clearly across the team. 

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That’s why we combine optimisation with explainable analytics and chemistry-first visualisations.

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And because the future isn’t just about experiment recommendations but about end-to-end workflows, we integrate ELNs, lab hardware, and analytics to enable closed-loop experimentation and, ultimately, self-driving labs.

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The goal is simple: faster robust conditions, shorter development cycles, and higher efficiency - with chemists firmly in control.

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See the full article here: https://www.google.com/url?q=https://www.5-ht.com/en/media/blog/ai-that-speaks-chemistry-how-reactwise-is-redefining-process-development&sa=D&source=docs&ust=1771269185317816&usg=AOvVaw0PuNEHPT7iBZr8dVCHOQo5

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