AI and Automation

For example, an AI assistant can act as your sales representative and take care of leads from a marketing campaign on your landing page and help convert the lead (entering the data in exchange for, for example, a lead magnet, service or voucher). ​ An AI Assistant can support new employees with SOPs, best practice and recommended procedures for new tasks. ​ The most effective and with the fastest return on investment is usually at the customer interface. ​ Recording service requests, appointment bookings, product questions, faults and providing answers to specific questions from your customers from its knowledge base make your AI an invaluable, never tired, error-free and motivated day and night supporter. In this way, you free up your employees for the really important inquiries and conversations, save costs and make more sales with more satisfied customers.

Synergies and cost savings arise where people no longer have to devote themselves to repetitive tasks. ​ With automations, their AI becomes the "agent" in the world. This has nothing to do with James Bond, but means your AI can act and interact with the outside world through actions. ​

These automations not only bring cost savings, but also open up new business models, business processes and improved communication quality with your customers. ​ We build the links between your IT systems and empower your AI assistant to initiate, execute and terminate actions and tasks through interfaces (API) and their use to other IT systems.

Machine learning algorithms are a broad field. From the algorithm for stock and options second traders to the algorithm that evaluates weather, machine failure, live production data, traffic and supplier data and can thus make a prediction about the expected purchase quantities and thus the quantities to be produced, and can also include local special events such as "European Football Championship match at the destination at the time of sale". Machine learning projects are worthwhile for more complex questions. Most importantly, it must be clarified where and how and in what quality and form your raw data is available. ​ Without data, everything is nothing. Also the algorithm.