# Alchemite™ for DOE ## Design of Experiments made easy **With Alchemite™, your team can apply the power of machine learning to ensure faster, fewer, better experiments.** Design focused experimental programmes, generate new insights, and collaborate more effectively – leading to cuts in experimental time of up to 80%. And all with no lengthy training courses, no need for advanced statistics, and no need for coding. [Free trial](https://intellegens.com/request-demo/) [Watch a webinar](https://intellegens.com/webinar-design-of-experiments-made-easy-with-machine-learning/) Our customers say... [We identified a route requiring **five times fewer experiments**\ \ **Johnson Matthey** found improved formulation designs for catalysts](https://intellegens.com/catalysts-for-clean-air-and-life-science-at-johnson-matthey/) [Alchemite™ could enable an **80% reduction** in direct testing costs\ \ **AMRC** studied manufacturing processes for an important class of composite material](https://intellegens.com/composite-manufacturing-with-the-amrc/) [We **improved performance** by 50% – and we were **able to get there faster**\ \ **FUCHS** applied Alchemite™ to lubricant formulation development](https://intellegens.com/fuchs-speeds-lubricant-formulation-development/) [Alchemite™ **reduced the formulation timescale** by\ months\ \ **Domino Printing Sciences** reduced timescales in development of new inks](https://intellegens.com/machine-learning-for-virtual-experiments-ink-formulation/) [We can **rapidly optimise process parameters** for new powders and machines\ Additive Manufacturing DOE with **AMRC**, **Boeing**, **Constellium**, and **GE Additive**](https://intellegens.com/data-driven-additive-manufacturing-with-amrc-and-boeing/) ## Faster learning Uncover new insights in a few button clicks. Alchemite™ offers an easy web user interface that helps you get the answers you need, faster – whether that’s uncovering improved experimental pathways, discovering better solutions, or understanding the **why** behind suggestions. [Watch webinar](https://intellegens.com/webinar-design-of-experiments-made-easy-with-machine-learning/) ## Fewer experiments Cut experimental workloads so that you can work on the things that matter most. Alchemite™ helps R&D teams streamline productivity – responding quicker to market changes and delivering reliable outcomes at lower cost, without disrupting existing workflows. [Read blog article](https://intellegens.com/why-use-design-of-experiments/) ## Better results Alchemite enables an _adaptive_ DOE approach that not only meets your objectives sooner, but can also find solutions that traditional DOE methods would miss. Apply trustworthy, proven technology that delivers results, along with valuable insights, while also supporting collaboration. [Read the white paper](https://intellegens.com/machine-learning-for-guided-design-of-experiments-white-paper/) ## Recommended Solution Individuals can pick the right Alchemite app for their R&D challenge. R&D organisations can match the right app to the right team member. Projects and results can be shared across all users, creating an integrated solution and enabling collaboration across your team. ### [Alchemite™ Designer](https://intellegens.com/solutions/designer/) Perfect for **scientists running experimental programmes**. Set up and run DOE projects in just a few button-clicks. Share recommendations and insights with colleagues. ### [Alchemite™ Viewer](https://intellegens.com/solutions/viewer/) **Managers** and other team members can explore project results and apply them in decision making. ### [Alchemite™ Architect](https://intellegens.com/solutions/architect/) **System architects** and **data scientists** can access the full power of the Alchemite ML method and integrate it into lab systems, analysis tools, and workflows. ## Further resources Find out more about Alchemite™ for Design of Experiments \ \ **Why you should combine DOE and machine learning**](https://intellegens.com/why-you-should-combine-doe-and-machine-learning/) \ \ **Why use Design of Experiments?**](https://intellegens.com/why-use-design-of-experiments/) \ \ **Machine Learning for Adaptive Experimental Design**](https://intellegens.com/machine-learning-for-guided-design-of-experiments-white-paper/) ## Alchemite™ for DOE - frequently asked questions... - #### What is the best software for Design of Experiments? There are many software options for supporting DOE. Most established software relies on statistical methods, which are good as a starting point when limited data is available, but can result in high experimental workloads and require statistical knowledge to ensure correct setup. Machine learning adds the ability to improve experimental designs by learning from existing data and, because it is data-driven, removes the need for the user to make decisions based on statistical insight. Alchemite Designer is an app designed specifically for machine learning-led DOE with an interface makes it quick to specify DOE projects, with no need for coding. - #### Why use machine learning in DOE? Machine learning (ML) enables an adpative approach to Design of Experiments in which each new experiment improves the recommendation for what experiment should be done next. This has been shown to achieve targets with 50-80% fewer experiments than relying on conventional DOE approaches. [Machine Learning for Adaptive Experimental Design](https://intellegens.com/machine-learning-for-guided-design-of-experiments-white-paper/) - #### How does Alchemite compare to standard DOE software like JMP? Machine learning (ML) complements standard DOE approaches. It can learn from data generated from initial experiments designed with these tools, enabling an adaptive, iterative approach to further experiments that gets to targets faster. ML is also good for exploring complex, high dimensional relationships and understanding what drives specific properties. You might find this white paper helpful: [Why you should combine DOE and machine learning](https://intellegens.com/why-you-should-combine-doe-and-machine-learning/) - #### Can you share examples of machine learning-led DOE? Clients we’ve helped include: **Johnson Matthey, AMRC, FUCHS Group and Domino Printing Science** Check out these case studies in the useful links below: [Catalysts for clean air and life science at Johnson Matthey](https://intellegens.com/catalysts-for-clean-air-and-life-science-at-johnson-matthey/) [Composite manufacturing with The AMRC](https://intellegens.com/composite-manufacturing-with-the-amrc/) [FUCHS speeds lubricant formulation development](https://intellegens.com/fuchs-speeds-lubricant-formulation-development/) [Formulation design with Domino Printing Sciences](https://intellegens.com/machine-learning-for-virtual-experiments-ink-formulation/)