Industry

Empowering Industrial engineers with AI.

Monolith is cloud-based AI software built from the ground up for engineers with an intuitive, easy-to-use UI designed for quick adoption and time to results for big data.

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Get in touch with Monolith

Trusted by industry experts :

“Monolith allowed us to understand and optimize the gas meter's behaviour for all operating conditions and optimize meter accuracy under extreme conditions, allowing us to build a superior, more accurate product in a much shorter amount of time.”

-Dr. Bas Kastelein, Sr. Director of Product Innovation, Honeywell Process Solutions

Packaging Optimisation Using AI With Aptargroup

In this exclusive customer webinar, Fabio di Memmo from Aptargroup & Monolith CEO Richard Ahlfeld talk about the value of Monolith’s no-code AI platform for packaging, and how to accelerate decisions from months to minutes.

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Optimising Particle Size and Shape Distribution From a Target Dissolution Profile With Nanopharm

A random forest regression model was trained to predict the mass dissolved at different time points from the size and shape of the particles, to a good degree of accuracy. The resulting Monolith dashboards enabled users to upload a target dissolution profile and return an optimized particle size and shape distribution that would produce the target dissolution profile.

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The Next Generation of Smart Meters Using Self-learning Models

Using Monolith to investigate test data, users can combine, transform and build self-learning models inside our no-code AI platform that accurately predict flow rates for multiple material types, through devices such as valves with varying throughput capabilities such as radius, length, and other relevant device measurements.

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Common Industrial engineering challenges

The time-to-market needs for industrial products and applications fail to meet customer expectations.

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Physical testing of every product iteration is expensive and time-consuming.

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Exploring and understanding a design space for all potential use cases is a time-consuming and inefficient use of resources.

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Case Study

The Next Generation of Pharmaceutical Development Using Self-Learning Models

A random forest regression model was trained to predict the mass dissolved at different time points from the size and shape of the particles to a good degree of accuracy. The resulting Monolith dashboards enabled users to upload a target dissolution profile and return an optimized particle size and shape distribution that would produce the target dissolution profile.

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Ben

Ben is a German-speaking science graduate who has spent over a decade working as an Account Manager at innovative software companies, supporting engineering organizations in understanding how adopting software solutions can accelerate and optimize engineering workflows.

Talk to an Expert

Talk to an expert

Resources

Learn how Monolith helps Industrial engineers test less, and learn more

Other industries

Automotive

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Aerospace and Defense

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Industry

Empowering Industrial engineers with AI.

Trusted by industry experts :

“Monolith allowed us to understand and optimize the gas meter's behaviour for all operating conditions and optimize meter accuracy under extreme conditions, allowing us to build a superior, more accurate product in a much shorter amount of time.”

Packaging Optimisation Using AI With Aptargroup

Optimising Particle Size and Shape Distribution From a Target Dissolution Profile With Nanopharm

The Next Generation of Smart Meters Using Self-learning Models

Common Industrial engineering challenges

Case Study

The Next Generation of Pharmaceutical Development Using Self-Learning Models

Talk to an expert

Ben

Resources

Learn how Monolith helps Industrial engineers test less, and learn more

Understanding Tyre Degradation Using Self-Learning Models

3 Ways AI Leaders Can Benefit From Self-Learning Models

The Next Generation of Smart Meters Using Self-Learning Models

AI Opportunities for the Battery Industry

How Can AI Guide the Optimisation of Antenna Designs?

Other industries

Automotive

Aerospace and Defense

Ready to get started?

We empower engineers to solve their most intractable physics problems.

Subscribe to our monthly newsletter

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Industry

Empowering Industrial engineers with AI.

Trusted by industry experts :

“Monolith allowed us to understand and optimize the gas meter's behaviour for all operating conditions and optimize meter accuracy under extreme conditions, allowing us to build a superior, more accurate product in a much shorter amount of time.” ​

Packaging Optimisation Using AI With Aptargroup

Optimising Particle Size and Shape Distribution From a Target Dissolution Profile With Nanopharm

The Next Generation of Smart Meters Using Self-learning Models

Common Industrial engineering challenges

Case Study

The Next Generation of Pharmaceutical Development Using Self-Learning Models

Talk to an expert

Ben

Resources

Learn how Monolith helps Industrial engineers test less, and learn more

Understanding Tyre Degradation Using Self-Learning Models

3 Ways AI Leaders Can Benefit From Self-Learning Models

The Next Generation of Smart Meters Using Self-Learning Models

AI Opportunities for the Battery Industry

How Can AI Guide the Optimisation of Antenna Designs?

Other industries

Automotive

Aerospace and Defense

Ready to get started?

We empower engineers to solve their most intractable physics problems.

Subscribe to our monthly newsletter

“Monolith allowed us to understand and optimize the gas meter's behaviour for all operating conditions and optimize meter accuracy under extreme conditions, allowing us to build a superior, more accurate product in a much shorter amount of time.”