Achieve the smart business transformation with artificial intelligence (AI)
Artificial intelligence is more than a marketing buzzword: it spells tangible advantages for companies. Intelligent software can be used to automate recurring processes in the area of knowledge work.
What does that mean in practical terms?
Automation is already a reality in manufacturing and production, facilitating massive productivity gains. However, artificial intelligence is also applied to knowledge work.
Algorithms free us from time-consuming tasks by, for example, automatically answering standard queries in customer service. This means you can devote as much time as possible to the important concerns of your customers. Artificial intelligence can also be used to perform demanding tasks such as giving suitable product recommendations to specific customers.
Our solution will help you automate your processes, optimize your products and services and target your resources at customers to maximum effect.
- Better resource utilization
- Greater customer satisfaction and customer retention
- Lower costs
- Increased sales
ORBIS supports your company on the road to smart business. We advise you on the AI transformation and help you seize the opportunities presented by artificial intelligence to generate profit for your company.
SMART BUSINESS IN THE REALIZATION
Machine learning is a significant step forward in programming. In contrast to traditional programming, the computer undertakes part of the programming itself in the case of machine learning. It learns from a wealth of data, for example by recognizing patterns and predicting values. As programs become less susceptible to error, tasks that could not be performed with traditional programming can now be realized.
Machine learning has three main areas:
1. Reinforcement learning
A machine learns by interacting with its environment through punishment and reward functions.
Example: driverless vehicles
2. Unsupervised learning
Machines identify patterns in large quantities of data without additional information on the data.
Example: Cluster analysis for customer segmentation
3. Supervised learning
When analysing a large quantity of historical data, the algorithm obtains an outcome that can be applied autonomously to future data.
Example: Spam filter
Deep learning, a special form of machine learning, uses neural networks and large data quantities. Such networks can be used to resolve complex tasks. For example, language, text and image recognition are based on deep neural networks of this kind.
We have a wealth of expertise in the field of machine learning and we offer professional advice and sophisticated products.
We help you do smart business with smart services and customized products for artificial intelligence
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