Digitization is leading to a constantly growing flood of data in companies. Information is spread across a wide variety of systems: from Nextcloud and network applications to CRM and document management systems. The challenge? Employees waste valuable time searching for relevant data. This is where AI solutions can make it much easier to access information within Nextcloud and beyond.
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What is Nextcloud?
Nextcloud is a powerful, non-commercial open source cloud software that allows users to create and manage their own secure and private cloud storage. As a fork of ownCloud, Nextcloud offers an alternative to commercial cloud services such as Google Drive, SharePoint or Dropbox. With Nextcloud, users can store, share and synchronize files and documents online and access a variety of integrated applications that increase their productivity. The software supports cross-platform Windows, macOS, Linux, Android and iOS and offers features such as file storage, calendar management, communication tools and online office software.
Why optimize Nextcloud with AI-powered search?
Nextcloud provides an excellent platform for file sharing and collaboration and also offers native search. However, native search solutions in many systems quickly reach their technical limits – they are often only a by-product and not a core function of a solution. This leads to challenges, especially in systems that have grown over the years, as less and less knowledge can be used efficiently. For example, the classic Nextcloud search only searches files within the platform and offers limited options for semantic analysis. AI-powered assistants can improve efficiency by:
- Linking content from Nextcloud with other company sources
- Prioritize relevant search results using NLP (Natural Language Processing)
- Deliver contextual results based on user behavior and patterns
The added value for companies quickly becomes apparent:
- Significantly better access to existing knowledge – always taking into account existing access rights as well as the GDPR and the EU AI Act
- Less search time and instead a deeper engagement with your own know-how Where previously time was spent searching, employees can now invest more time in value-adding activities and thus deliver better quality results.
- Less duplication of work – employees build processes on existing knowledge instead of developing it twice.
This enables companies to make existing knowledge within Nextcloud much more accessible to their employees.
Different search technologies make the difference
Until a few years ago, keyword-based solutions were used exclusively, but new, AI-based technologies have opened up completely different possibilities. Until a few years ago, you had to hit the keyword exactly, but now semantic similarities are enough to find suitable documents. This means that information can be found more easily, especially with imprecise terms. This blog article explains how the various search technologies differ in detail.
Cross-system integration: all information in one place
So far, we have primarily written about how an optimized search within Nextcloud optimizes information processes. However, an isolated search in Nextcloud does not solve the problem of fragmented data sources. If we develop this idea a little further, we quickly arrive at a kind of “Google for the company”, which enables employees to find information across systems. The technical term for such a system is “enterprise search”:
- File servers, intranet, document management systems, CRM and many other systems can be connected
- A good enterprise search can recognize duplicates and aggregate content intelligently
- In addition, authorizations are taken into account to ensure data protection and compliance with the GDPR
Seamless integration allows users to find all relevant information – from any source – with a single query. This leads to greater productivity and a better basis for decision-making. An example of what such a search can look like is shown in this video:
Even if a Nextcloud integration is not explicitly shown in this video, it quickly becomes clear how the added value of AI can be realized within a Nextcloud environment.
Integrating the AI assistant into Nextcloud
The fact that the information must be indexed (not text-based, but vector-based) for an AI-based enterprise search, as shown above, already provides the perfect basis for cross-system AI assistants. In the next phase, employees can use a retrieval augmented generation system to chat with the company’s internal expertise and build their own AI assistants. This means that internal knowledge is also easily accessible via AI – regardless of the data silo.
Integrate Nextcloud AI: How it works
The implementation of an AI-supported enterprise search in Nextcloud takes place in relatively simple steps. The integration of the amberSearch solution was used as an example to describe the process:
- Register amberSearch as an app: First, amberSearch must be registered as an app (depending on the system, this also works with a correspondingly authorized service account. This step must be carried out for each system that is to be connected. On-premise systems are connected via a site-to-site IPSec VPN, as amberSearch is usually obtained as a managed service.
- Indexing: Indexing is started automatically based on the released content. This is necessary so that the AI “knows” the company know-how. Important: This is not the training of AI models with customer data, but the preparation for the retrieval augmented generation process mentioned above.
- Integration into existing interfaces: To give users the best user experience, amberSearch can be integrated where employees work on a daily basis – as an IFrame integration, as a chat widget or as a desktop app.
This is how companies can create AI within their Nextcloud environment in just a few steps.
Gain initial experience with AI in Nextcloud
If the topic sounds exciting or promising overall, then we look forward to hearing from you. We would be happy to support you with the introduction of AI in your Nextcloud environment: