CSB AI Assistant
Cesy: interacting with your ERP data
Leverage data. Speed up decision-making.
Today’s businesses have unprecedented access to high-quality data sources: ERP systems are well-established, data availability is ensured, and reports are widely accessible. It is now a matter of unlocking this potential in day-to-day operations. In particular, when you need to make ad hoc decisions.
This is where Cesy comes in: With the AI assistant, analyzing your data is as simple as chatting. It instantly translates your questions into actionable results.
Ask questions and get instant answers
Interact with your ERP data using natural language
Accurate data for confident decisions
Rethinking self-service analytics and query strategies
Cesy is there to assist you when time is critical. You can simply ask ad hoc questions on turnover, customers, products, or internal knowledge directly in a chat.
Cesy processes your input, analyzes your ERP data and your internal knowledge base with RAG, and returns the desired results within an instant. This transforms your ad hoc question – for example, on a customer’s turnover in the last quarter – into structured insights. You can then refine your initial questions to formulate more detailed queries.
Frequently asked questions about Cesy
Cesy is an AI assistant for self-service analytics in an ERP environment that allows you to interact with internal business data as if you were chatting with a coworker. It provides quick and easy-to-understand answers to spontaneous questions.
You ask Cesy a question in natural language. For example, “Show me the turnover of our top five items in the last quarter as a chart”. Cesy analyzes the available data and prepares the desired visualization form, providing a straightforward explanation of the result.
With Cesy, you get instant results and clear insights, without requiring SQL knowledge or complicated workarounds. This allows you to make fast and informed decisions.
Yes. Cesy enables you to scale and adapt standardized analyses of turnover, sales, or suppliers as iterative use cases.
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