Initial situation
An established provider of banking software was faced with the strategic challenge of making its support processes more efficient and future-proof existing products. In view of complex support requests and high response speed requirements, the company was looking for ways to integrate modern AI technologies in a value-creating way. The central question was whether and how generative AI could effectively relieve support staff and whether the investment in their own AI assistant could be economically justified.
Our solution
AMAI supported the customer in a structured consulting process to assess the feasibility and profitability of an AI-based support system. The focus was on a neutral and data-based analysis that goes beyond pure technology hype.
The consultation process included the following steps:
Exploration and use case sharpening: In joint workshops, various application scenarios for AI in the support environment were identified. A RAG-based system (retrieval-augmented generation) was defined as the most promising approach, which should support support staff by automatically providing information from ticket histories and documentation.
Technical architecture design: AMAI developed a sustainable technical concept for the identified use case. This included the use of large language models in a secure cloud environment such as Microsoft Azure, the connection to existing ticket systems and mechanisms for quality assurance of AI answers. Particular attention was paid to meeting industry-specific compliance requirements.
Detailed profitability analysis: The core of the consultation was the preparation of a comprehensive business case. The forecasted development costs and ongoing operating costs were compared with the expected efficiency gains in support. This analysis provided a transparent calculation of the return on investment (ROI) and assessed qualitative factors such as employee satisfaction and service quality.
Results & business impact
The project provided management with a well-founded and reliable basis for decision-making for the further AI Strategy. The detailed review of all technical and economic aspects gave the customer full transparency about the opportunities and risks of the project.
The business case enabled the company to make investment decisions based not on assumptions but on the basis of hard facts. The detailed analysis provided clarity about the necessary requirements and the expected benefits, which allowed precise strategic planning and prioritization of innovation projects in the support sector.
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