Artificial Intelligence:
When data starts to think

Artificial intelligence and automation: unbeatable together

Why Artifical Intelligence? With a state-of-the-art CRM system, companies can collect and manage customer data. Yet, how can they use the data in a meaningful way? ML algorithms are like data detectives that help search through the mountains of data and make them useful. This is how marketing, sales and service benefit from the power of AI: smarter customer support, smarter service for potential customers, a greater degree of efficiency, and unimagined opportunities in terms of the customer experience.

From churn detection to lead scoring

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Sentiment analysis

Smarter support in complaint cases, social media monitoring, etc.

Decision support

The suitable “brain” does the job, whether it comes to churn detection or lead scoring.

Text and image recognition

Improved efficiency and better clarity with automatic image tagging or handwriting recognition on forms.

Fraud Detection

Unusual account transactions or irregularities on salary statements – any abnormal customer behavior is quickly uncovered.


Next Best Actions, the best communication channel, the appropriate point in time to reach out to your customer – AI knows the Where, the Why, and the How.

Relevant correlations

Weather and travel arrangements. Interests and orders. Age and communication channels: “Brains” can detect relevant correlations.

What is artificial intelligence (AI)?

With artificial intelligence (AI), developers try to simulate “intelligent” behavior with computers. The term “machine learning” (ML) refers to a collection of algorithms that make predictions based on experience in the form of data. Neural networks are one type of algorithm that uses biological neural networks as a model.

"With BSI Brains, our customers can benefit from the power of AI without our support and without data scientists, and they can use neural networks that were previously available exclusively to data giants for their own purposes "

Christoph BräunlichML expert atBSI

BSI Brains: More intelligence!

More intelligence in customer relationship management! With BSI Brains we democratize. The AI solution allows marketing, sales and service managers to use artifical intelligence easily and efficiently for their projects. Seamless integration with CRM and BSI Studio, our marketing automation platform opens up a whole new world of proactive, real-time, on-demand customer communications.

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Modular-design AI

With BSI Brains, users can design self-learning AI workflows and configure neural networks. Brains are easy to assemble via flexible drag-and-drop and can implement, for example, text or image recognition, churn detection, or the dynamic arrangement of content on a landing page or in an e-mail newsletter without any external support.

Our strengths

  • Modular-design AI: Users can easily click the Brains together by using the mouse. Then, they can incorporate the completed, trained Brains directly into customer journeys in BSI Studio.
  • Road-tested AI: BSI Brains ushers machine learning into day-to-day business. To accomplish this, BSI has developed specific use cases for their customers using customer data.
  • Quick benefits from AI: In addition to end-to-end machine learning, BSI depends on transfer learning in combination with traditional data science. This allows companies to get started quickly and without a major training effort.
  • Integrated AI: The data from the CRM or marketing automation solution is incorporated into the Brains thanks to seamless integration.

Will AI benefit you, too?

Would you like to find out how companies can benefit from artificial intelligence? We have the answers for you – answers from real people.

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Who benefits?

  • Marketers: AI power with a click of the mouse? It is as simple as it sounds. In BSI Studio, there are various “brains” available to be used as steps in the customer journey design. They handle tasks from lead scoring to churn detection.
  • Marketing technologists: With the graphical Brain Editor, development components of ML steps that would normally have to be programmed can be assembled by drag-and-drop.
  • Data scientists: The inner workings of “brain” blocks can be configured if knowledge is available about neural networks or genetic algorithms