Getting started

 

Get started with AI

Solve your most intractable physics problems.

BMW
BAE Systems
Mercedes
Honda
Siemens
Kautex-Textron
Michelin
Aptar
Jota

Getting started with Monolith:

The AI adoption journey

 

Our team of engineers, software developers, and industry veterans bring decades of combined experience working with the world’s top engineering teams to ensure 100% customer success. We are your trusted partner to use AI to develop the highest quality and best-performing products, faster.​ 

customer service
High-touch support and guidance
Coral - test plan optimize
Built-in tutorials and training
work smart not hard
Project experience to deliver success
The AI adoption journey: crawl
  • Define a problem to start with
  • Reduce your scope
  • It’s a team game
  • Test the capability
  • Learn a new skill
  • Work out where to go next
getting started crawl
The AI adoption journey: walk
  • Expand your problem scope to other areas
  • Start standardising your data
  • Improve your models
  • Embed AI in your workflow
  • Share your journey with others and grow your team
walk with monolith ai no code software
The AI adoption journey: run
  • Integrate into the infrastructure
  • Productionise AI
  • Bring your customers in on the fun!
Dashboard - Vehicle Benchmarking (1)

Technical requirements for AI

1
Methods to capture and store data

When it comes to adopting Artificial Intelligence (AI) for engineering applications, one question that is always asked is “how much data do I need?”

2
Finding the right AI use case for you

Companies are not using AI because they don’t understand what it can be used for or don’t see a clear application in their work.

Companies that attempt to use AI often fail due to misunderstanding AI and its applications. We help you find your ideal use case for AI.

3
Organisation structure: assigning a champion

AI has become a mainstream topic in product design and engineering. Monolith is helping all types of engineering companies to understand how ready they are for AI, to take those first steps towards adoption, and to realise its benefits at scale. 

 
Kautex-Textron webinar

 

Use AI to predict fuel-sloshing noise, solve intractable physics

 

  • Problem: vehicle acoustics 
  • Methods tried: CFD, physics-based simulation
  • Solution: predict noise, reduce testing with self-learning models
Welcome pack

 

Download our customer welcome pack to learn more about: 

 

  • project teams 
  • how to find a great use case 
  • introductions to typical use cases 
  • information around data needs & feasibility 
  • success metrics 
    ...and more!
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New feature

 

Next Test Recommender (NTR): AI-powered test plan optimisation

Learn how our AI software's latest feature enables users to train and assess machine learning models. It offers valuable recommendations for optimal test conditions to apply in the next round of testing. NTR assesses previously gathered data to suggest the most effective new tests to conduct. 

Solving complex physics across aerospace and defence, automotive, and industrial sectors

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Customer success: onboarding, training & value-focused projects

it installation

IT installation options & security credentials

 

customer service

Customer service management via our user-friendly support portal

research and collab

Research collaboration opportunities through enlisting our data science team & product research

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Software security credentials 

  • ISO 27001 Certified
  • GDPR Compliant
Michelin
quote_marks

“The Monolith team understood what it means to work with genuine engineering problems in artificial intelligence: the needed flexibility and knowledge.”

- Joachim GUILIE, Curing performance expert at Michelin

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“It's a team with a very good personal relationship.”

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“The Monolith AI team is excellent.”

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“The best thing about this software is the team. All the team members are experienced and always available to help and solve the issues”

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“They are prompt with communication, well organized, really know their stuff, and are good at communicating with non-experts in their field.”

Ready to get started?

BAE Systems
Jota
Aptar
Mercedes
Honda
Siemens