aixioom corporate.autoAI
Imagine being able to use artificial intelligence (AI) with just one click, in an automated way, without any prior knowledge of data science, and to use the values contained in your data quickly and easily. Our solution analyses your data and selects the algorithm best fitting your data from a library and trains it automatically.
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Our software aixioom corporate.autoAI offers you exactly that:
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Sample industries and use cases:
- Predictive Maintenance
- Early fault detection (prediction of tool breakages in real time)
- Root cause analysis in production
- Aerial image analysis for the creation of environment maps for autonomous driving
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- Prediction of customer orders in distribution logistics
- Prediction of shipment quantities
- Condition monitoring for transport
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- Dynamic Pricing
- Prediction of sales volumes
- Personalised purchase suggestions (other customers also bought)
- Optimisation of customer service
- …
- Automatic validation of financial transactions
- Detecting irregularities in financial data (fraud detection)
- Invoice processing and reimbursement in insurance
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Frequently requested use cases
The recognition of objects on images can be carried out with the help of image analysis. For example, cameras, X-ray or infrared devices can provide data in the form of images, which can be analysed for certain patterns, such as a scratch on a lens.
In marketing, for the creation of personalised purchase suggestions, different target groups are identified within customer data and their preferences and inclinations are predicted.
In the field of mechanical and plant engineering, predictive maintenance can be used to better predict machine failures and thus make it easier to plan maintenance and servicing.
Root cause analysis can for example find the cause of an unexpected error in production based on machine data.
Stack of technology
Application Platform
Accelerate AI application development for cloud, on-premise, or hybrid infrastructures.
aixioom corporate.autoAI
Automated creation and deployment of AI models.
Database layer
Collection and aggregation of all relevant data and the values it contains, from the lower layer.
Data generation
The data created in this layer can be in the form of structured data (e.g. tables), unstructured data (e.g. communication) or semi-structured data and originate from processes (e.g. in ERP or CRM systems), e-mails, images or texts.
