AI chatbot enables self-service BI
Chapter Lead Data & Analytics // Aachen Real Estate
Find out more about the success story with Aachen's real estate
Read in our case study how, together with Aachener Grundverät, we have provided employees with easy access to data through the AI Analyst, while relieving IT of routine issues.
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Find out more about the success story with Aachener Grundvermögen
Read in our case study how, together with Aachener Grundvermögen, we have provided employees with easy access to data through the AI Analyst, while relieving IT of routine issues.
Please note: All casestudies are available in German only.
Initial situation
Aachener Grundvermögen has a modern, scalable data warehouse, which serves as a central database in the company. Nevertheless, all reporting and analysis requests, in particular short-term ad-hoc queries, continue to run centrally via the data and analytics team. This results in high coordination costs, long waiting times and a heavy burden on the specialist department. At the same time, employees want easy access to data without having to use technical knowledge or additional tools.
High number of ad-hoc data requests
Dependency on the data team
Long waiting times from request to answer
Our detailed approach
Data connection & knowledge base
For the AI Analyst, all relevant data sources of Aachen's real assets are centrally connected to Snowflake. At the same time, Confluence creates a knowledge base with KPI definitions, synonyms, business logic and company-specific terms. In this way, the bot understands the company language and can answer contextually.
AI Analyst Development
Based on Azure Bot Services, Azure OpenAI and a validated SQL engine, we develop the AI chatbot. It receives questions in natural language, generates appropriate SQL queries, checks them syntactically and semantically, and returns results directly from Snowflake. Integration with Microsoft Teams enables seamless use in everyday work.
Testing, optimization & quality assurance
A selected group of employees is testing the AI Analyst in a controlled pilot phase. Your feedback flows directly into the development process. Through continuous optimization of prompt logic, knowledge base and SQL rules, response quality is continuously improving. In addition, logs are analyzed in Snowflake to identify misinterpretations and potential improvements.
Integration & rollout
After successful tests, the AI Analyst is fully rolled out into Microsoft Teams. A secure architecture in the Azure cloud ensures data protection and GDPR compliance. Employees now benefit from immediate, automated queries.
Conversational BI: Efficiency gain in reporting through the use of AI Analyst
By using AI Analyst, data and analytics employees can focus more on complex analyses and strategic issues instead of investing time in repetitive ad-hoc evaluations. This not only increases the quality of data work, but also team satisfaction, as routine inquiries are significantly reduced. At the same time, departments benefit from faster answers and greater independence. As a result, Aachen's real estate gains efficiency and can use its data resources significantly better and in a more targeted manner.
We are looking forward to your request and are excited to see what you have in mind. With us, you'll be met with open ears, let's get started with your AI project right away. Just tell us what you need!
