AI Chatbot for internal documentation

Q: Does our data stay in-house?

Yes, if you wish: The solution can be operated entirely locally and on-premises, using open-source language models on your own hardware. This makes it suitable even for sensitive system environments and high security requirements.

Q: What types of documentation can be integrated?

Typical examples include SAP project documentation: business concepts, technical specifications, customizations, deviations from the standard, and project decisions. The principle works for any internal corporate knowledge repository.

Q: What’s the best way to get started?

With a clearly defined knowledge area, such as the documentation for an ongoing SAP project. In the AI Kickstart Workshop, we’ll work together to identify the use case that offers the greatest benefit to your team.

Why is internal knowledge so hard to find?

The answer has long been somewhere in your documentation. But where exactly? Scattered files, overgrown folder structures, and search functions that only recognize filenames – that’s how a quick query can quickly turn into half an afternoon. This hits new colleagues during onboarding and anyone working on complex tasks the hardest. The result: Valuable work time is spent searching instead of solving problems. This is exactly where a chatbot-powered expert system comes in: It understands the question, searches your entire documentation, and delivers the answer – with a source reference – in seconds.

How does the chatbot answer questions from your documentation?

The chatbot-based expert system offers an efficient and precise way to quickly find and use information in the knowledge base and generate answers in natural language.

AI-powered document analysis: Modern image recognition algorithms efficiently search the entire internal knowledge base and identify relevant documents based on user queries

Intelligent natural language processing: A language model understands the query in context and extracts the necessary information from the documents found.
Context-sensitive response generation: The AI accurately summarizes the relevant passages and responds in natural language, with transparent references to the underlying sources.
Local data processing: The chatbot runs on local hardware using open-source language models, if desired. Sensitive company information never leaves your premises.

Practical example: Leveraging SAP project knowledge

Over time, SAP projects generate an enormous amount of documentation: business concepts, technical specifications, customizations, deviations from the standard, and project-specific decisions. This knowledge is extremely valuable for operations, but in day-to-day work it is often difficult to access, scattered across numerous documents, and far removed from standard sources or public knowledge.

abat develops LLM-based chatbots with Retrieval-Augmented Generation (RAG) that make precisely this project-specific knowledge usable. The chatbots “know” the entire relevant documentation, search it specifically, and provide context-sensitive, precise answers to questions from business units, IT, or operations, tailored to the respective SAP system and the individual project implementation.

In doing so, the chatbots access only internal company content. Answers are always derived from existing documentation and are traceable, as the underlying sources are transparently referenced. This builds trust in the results – even for complex or critical issues.

Whether in a project, during go-live support, or in day-to-day operations, the chatbot becomes the central knowledge hub for SAP-specific expertise that would otherwise be difficult to access.

Key benefits at a glance

Project and specialized knowledge available at any time, eliminating the need for lengthy searches through documents
Answers from your own SAP documentation – traceable and with source references
On-premises and data-secure, even for sensitive system landscapes

Advantages and benefits

Significant time savings:
Research takes seconds instead of hours.

Higher productivity:
Employees focus on core tasks instead of searching for information.

Better decisions:
Relevant data is immediately available – enabling well-informed, quick decisions.

Faster onboarding:
New employees get up to speed quickly and independently.

Access to knowledge for everyone:
Equal access to knowledge –regardless of role or experience.

Data security:
Local open-source solutions protect confidential company data.

Make your project knowledge accessible

How much time does your team spend searching for information that has actually been documented for quite some time? Talk to us – we’ll show you how a RAG chatbot works using your own documentation.

A chatbot for your knowledge management is the perfect way to get started with AI-Shore. Our methodological approach expands this solution into a comprehensive system that structures knowledge, streamlines processes, and lightens the load on teams. Discover how AI-Shore turns your chatbot into a real productivity booster.

Frequently asked questions about the AI Chatbot for internal documentation

How does the chatbot know the answer?

Exclusively from your own documentation. The chatbot searches the internal knowledge base, derives the answer from the documents it finds, and transparently cites the sources. It does not generate content based on publicly available information.

Does our data stay in-house?

What types of documentation can be integrated?

What’s the best way to get started?