Internal AI chat for your company knowledge

Our solution supports a variety of sources: cloud storage like Google Drive, OneDrive, and Dropbox; websites/intranets—such as your company wiki, knowledge base, or SharePoint—as well as files (PDF, Word, Excel, PowerPoint, and many more) that you provide us. We configure dedicated connectors for each agreed data source so that the assistant can index and search the content. Additional systems (e.g., databases, CRM) can be integrated via add-ons.

Data security is our top priority. All data remains exclusively within your infrastructure – no data is transferred to unauthorized third parties. An internal AI chat is operated in a closed environment, ensuring no confidential information is leaked. Our solution is fully GDPR-compliant and can be hosted on servers in Switzerland/the EU if required. Access is encrypted and role-based. Upon request, we offer an add-on for on-premises installation or enhanced security measures.

You can integrate the knowledge assistant via chat platforms like Slack or Microsoft Teams—for example, as a chatbot that can be @mentioned in channels. Web chat integration is also possible (for example, on your intranet page or helpdesk portal). This ensures that your users access the service exactly where they need it.

By default, an internal AI chat is configured for one language (e.g., German). However, the assistant can be configured for multiple languages upon request – we offer the *Multilingual Assistant* add-on for this purpose. This allows requests and documents to be processed in multiple languages. The AI recognizes the language of the request and provides answers in the same language. This allows you to cover German and English content simultaneously, for example.

The monthly price includes everything – including setup, maintenance, and support. Any usage costs for connected AI services (e.g., API requests or storage) are also covered, as long as they remain within normal limits. You don't have to worry about anything else – we take care of reliable operation for you.

Yes, if you don't want to use the cloud for compliance reasons, an on-premises deployment is possible. In this case, the solution is installed in your data center or private cloud, and all components (database, search index, AI models) run under your control. This scenario requires additional effort for installation and configuration. With on-premises, you retain full data sovereignty, but you must provide the appropriate server infrastructure.

A conventional search usually compares precisely entered keywords with the database. Semantic search, on the other hand, understands the context of the query. This means it also recognizes synonyms, connections, and the intent behind a question. This allows it to deliver relevant information even if the user doesn't use the exact keywords. In short: Semantic search delivers more precise and contextual results, while keyword-based search only filters for word occurrences. This leads to a significantly better search experience for users.