scientia tech

AI from process industry experts, for process industry experts

Our solutions will improve production efficiency, save energy and money while offering ROI of only 1-3 months. Let’s talk to find out how we can help.  

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Mechanistic AI - Smarter Digital Twins

Do you struggle with any of the following challenges in your production?

1. Wasting energy making products excessively pure due to lacking or infrequent measurements, just to be safe?

2. Observing variations in product quality and having difficulties controlling the plant, but cannot find the source for these problems?

3. Plant cannot react fast enough to changing conditions, e.g., feedstock composition since outcomes of control actions can be seen with a delay?

Mechanistic AI can fix them all and is industry proven! ROI within 1-2 months!

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Process Autopilot

Process Autopilot can help with:

1. Struggling with excessive product quality variations operators cannot keep up with?

2. Production is affected by disturbances, e.g., feedstock composition, outside temperature and operators struggle to counteract them?

3. Producing excessive waste due to frequent changes in required product quality or changes in product type?

Superhuman production optimization. Proven technology with fast and guaranteed return on investment.

Our Team

We started this company because of the frustration with the AI solutions offered to the process industry. These solutions did not scale past proof of concept phase, did not offer a reliable predictions and rarely worked at all. Our mission is to offer solutions which minimize energy and production cost, as well as are affordable and reliable.

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Alexander Bor

D.Sc. in process control and automation from Aalto University focusing on optimization of energy boilers. Worked in industry leader companies such as Neste, Wärtsilä and RELEX Solutions. Several years of product management and algorithm development experience of industrial optimization products. Extensive knowledge in both continuous and discrete optimization as well as machine learning methods. OPC UA proficient.

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Alexey Zakharov

PhD in applied mathematics from Moscow State University. Proven track record of developing state-of-the-art process control and predictive maintenance methods which are both robust and data efficient. Broad experience in successful implementation of machine learning and predictive maintenance solutions in various industries.

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What Clients Say About Us

The project aimed to create an advanced model by utilizing data in combination with physical and chemical principles, to be capable of estimating the purity of the bottom product in a distillation column. This model offered valuable insights into the column's operation, revealing a deeper understanding of the underlying process. Scientia Industrial Technologies demonstrated extensive expertise in process technology throughout the project. They showcased their ability to gain a thorough understanding of the complexities within the distillation process and effectively integrate this knowledge into the model, allowing it to uncover relevant aspects.

Mohammed Adlouni, Senior Specialist, APC and Analytics, Perstorp AB
We recently collaborated with ScientiaTech to analyze the improvement potential of our vacuum distillation column. Their team demonstrated exceptional process understanding and analytical skills, successfully identifying key factors leading to increased process profitability. We were impressed by their expertise and look forward to continuing our partnership on future projects.

Lukas Vikander, APC engineer