In-house AI chatbot – efficient knowledge management through retrieval augmented generation

How an AI-supported chatbot based on RAG is revolutionizing internal document searches and automating support tickets.

Customer

Customer benefits

Technology stack

"jovoco's solution has taken our internal knowledge management to a new level. Instead of laboriously searching for documents in various systems, our employees now receive the information they need quickly and in a targeted manner - directly in the work context. We have noticed a clear increase in efficiency, especially when processing support tickets."

Head of IT

Challenges of the customer

The company had a large number of internal documents distributed across different storage locations such as SharePoint, OneDrive and internal network drives. The decentralized storage of information made it difficult for employees to access relevant content quickly – especially when dealing with time-critical inquiries or processing support tickets.

The result: delays in work processes, inefficient information searches and a high level of manual effort in internal communication.

The company was therefore looking for a central, secure and intelligent solution to make existing knowledge available in a targeted manner – ideally without employees having to actively click through document structures.

Our approach

In close cooperation with the customer, we have developed a customized RAG solution that can be seamlessly integrated into existing systems and is specifically geared towards real-life use cases.

Requirements analysis & target definition

At the beginning, we worked with the customer to identify the existing data sources, processes and weak points in the use of information. From this, we derived clear project objectives - in particular the automated provision of knowledge and efficient integration.

Data connection & document preparation

We bundled, structured and prepared data from SharePoint, OneDrive and other sources. This enabled us to optimally prepare the content for semantic search and AI processing.

Development of the RAG architecture

An individual backend has vectorized the documents and provided a powerful RAG logic. Users not only receive direct answers, but also the appropriate document sources - for maximum transparency.

Integration into existing workflows

We integrated the solution directly into existing tools such as Microsoft Teams and internal ticket systems. Employees can now access relevant information in their familiar environment without any detours.

Test phase & continuous optimization

After a test phase with real use cases, we gathered targeted feedback, trained users and iteratively improved the solution until it was optimally suitable for everyday use.

Results for the customer

Documents integrated into the AI

> 0 .000

Reduction in ticket processing time

Further results:

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