AI. Innovation. Everything in between.

Let working, intelligent, self-improving bots make initial connections with leads 24/7. High-quality, responsive leads are called by live agents and increase sales effectiveness.

Bots listen to calls from salespeople and suggest best practice answers or the best next steps to improve sales effectiveness.

Intelligent allocation of shipment requirements. Based on a customer's needs and location, the best warehouse is selected for shipping.

Price optimization, also known as dynamic pricing or demand pricing, enables companies to optimize price reductions. Optimal discounts minimize cannibalization and maximize revenue at the same time. Dynamic pricing is one of the easiest transformations a company can achieve. They have a direct effect on the end result and can be introduced within a few days.

By creating connections between different goods, which are typically ordered together, commission times can be drastically reduced.

Recommendation systems use customer data to retain and improve customers with personalized recommendations via email, website search, or other channels.

To prevent malfunctions or poor maintenance from leading to expensive downtime, an algorithm predicts the risk of equipment failure and the need for maintenance.

AI can predict service cases and thus increase accuracy when planning service and maintenance.

Use machine learning to take your inventory and supply chain optimization to the next level

Predicting energy demand and managing energy production.

By using entity and sentiment analysis, emails can be automatically classified, which requires up to 40% less manual work.

With the help of chatbots, companies can create a kind of more dynamic FAQ page or use it internally as a tool to increase the productivity of their own employees.

Financial risk scoring

Independent coordination of tasks, status updates and dependencies, with clear transparency for project managers.

AI analyses legacy code, suggests modern architecture and technology approaches, and supports developers in automated migration to sustainable systems.

AI analyses studies, suggests new hypotheses and plans experiments — researchers decide on next steps.

AI analyses documents, compares them with guidelines and suggests decisions — the administration makes the final decision.

Automated monitoring of clusters of side effects in patient feedback, forums, or EHRs, e.g. after the launch of a new drug.

Extraction of relevant information from emails, forms or photos to pre-qualify liability and comprehensive claims.

NLP analyses doctors' letters and clinic reports for clarity, risks and medical advice for more structured communication with patients.

Machine learning classifies hospital cases faster, comprehensibly and auditable for billing and quality assurance.