From repeated visitor questions
to an AI-powered WhatsApp front desk.
A Danish cultural association received recurring questions from visitors about practical matters, activities and the organisation. Because the information and circumstances could change over time, a static FAQ was not enough. SR Konsul built a WhatsApp-based AI assistant designed to answer questions using the association's own knowledge and be refined over time using updated information, real visitor questions and feedback.
The challenge
The association received many recurring questions from visitors about practical matters, activities and other organisation-specific information. Answering the same types of questions manually created repetitive work, but simply publishing a longer FAQ would not solve the underlying problem.
Many questions were contextual rather than identical. Visitors could phrase the same question in different ways, ask follow-up questions or need an answer based on specific information about the association.
The conditions behind some answers could also change over time. This made a static question-and-answer library difficult to keep useful on its own. The challenge was therefore to create a conversational layer that could use the association's knowledge while remaining adaptable as the underlying information evolved.
The approach
SR Konsul identified the types of questions visitors were asking and the knowledge required to answer them responsibly, then structured the association's relevant knowledge for an AI-based assistant connected to WhatsApp.
The solution was designed to understand questions phrased in different ways, identify the relevant information and return a useful response directly in the conversation — handling recurring questions that could reasonably be answered from the available knowledge, without removing human involvement entirely.
An important part of the work was iteration. An AI assistant like this is not effective simply because it has been launched. Its usefulness depends on the quality and coverage of its knowledge, the questions it encounters and the feedback used to refine it. This is also why SR Konsul does not recommend AI by default: the use case must justify the additional complexity compared with a simpler FAQ or contact flow.
The impact
The association now has a WhatsApp-based conversational layer through which visitors can ask practical questions using natural language rather than having to identify the exact wording used in a static FAQ.
Recurring questions that can be answered from the association's available knowledge can be handled through the assistant, while questions requiring judgement, unavailable information or human attention can remain outside the automated flow.
More importantly, the solution created a foundation that can become more useful over time. New visitor questions, changes in the association's information and observed gaps in responses can be used to refine the knowledge and improve the assistant.
The case demonstrates where conversational AI can create value — but also why implementation should begin with the underlying information, use case and process rather than with the technology itself.
Have a similar challenge?
Tell us briefly what needs to work better. We'll determine the right next step.