For organisations, this is an important step: instead of acting only once employees are already experiencing problems in their day-to-day work, administrative measures can be initiated earlier and planned more effectively. This not only supports operational stability, but also reduces unnecessary interruptions and coordination efforts.

The main benefit is therefore at an organisational level: processes become easier to plan, responsibilities are better supported, and operations become more robust overall. For users, the feature largely remains in the background—and that is precisely its strength. After all, good administration is often most evident when problems never become visible in the first place.

AI-Assisted Prompt Editor

In practice, one thing quickly becomes clear with Prompting: the quality of the results depends largely on the quality of the input. At the same time, formulating effective prompts can be challenging — especially when complex use cases, various dependencies, multiple data sources, or intermediate results need to be taken into account. Not every prompt can be structured perfectly on the first attempt so that the model fully understands and processes the actual task in the best possible way.

This is exactly where the AI-assisted Prompt Editor comes in. It provides users with convenient support for refining existing prompts, structuring them more clearly, and optimizing their content so that the desired output quality is more likely to be achieved. This makes working with generativer KI not only more efficient, but also more accessible and reliable.

The value of this feature is particularly broad: in principle, it is aimed at all users, since Prompting is the central element of every interaction with an AI model. However, people with little or no prior experience benefit especially from the additional support. They are given an easy and accessible way to develop effective prompts, avoid common mistakes, and no longer have to constantly keep best practices and pitfalls in mind on their own.

For VARIOS AI, this marks an important step toward an even more user-friendly platform: the barrier to the productive use of generative AI is significantly lowered, uncertainty in working with prompts is reduced, and more users are able to achieve high-quality results — even without deep Prompting know-how. The AI-assisted Prompt Editor therefore helps to sustainably increase quality, user-friendliness, and acceptance in the daily use of AI.

A language model is only as good as the data it can access. Until now, using your own knowledge bases often meant a compromise: either high manual maintenance effort or the risk that the AI relies on outdated information.

With the new Auto‑Sync we solve this dilemma.

You can now connect sources such as Nextcloud (via WebDAV), GitHub or your local network folders directly to VARIOS AI. You define the schedule, we take care of the rest: at fixed intervals the system checks your sources, detects changes and automatically updates your vectorized knowledge database.

What this means for you:

• No outdated data: Your assistants always answer based on the current reality.
• No manual effort: Manually uploading and vectorizing new file versions is completely eliminated.
• Independence: Use state-of-the-art vector search even for data that is not stored in an API-capable cloud.Your data stays where it belongs – but the knowledge within it is always fresh and available for your AI.

Not every question requires the same depth of search. With the new advanced search configuration, we provide you with the tools to precisely control how VARIOS AI processes information from your documents. You decide how the AI searches and how much context it considers.

Your new possibilities at a glance:

• Variable Chunk Size: Determine for yourself how large the text segments (chunks) sent to the language model should be. Smaller fragments ensure pinpoint answers to specific questions, while larger sections provide more context.
• Flexible Search Strategies:
  • Semantic: The AI searches for meaning and context (ideal for open-ended questions).
  • Literal: The AI searches for exact terms (ideal for part numbers or fixed definitions).
  • Hybrid: Combine both methods for the best possible results.

By decoupling document processing and offering the option to use local embedding models, the risk of data leakage is minimized. In addition, the new processing of anonymized documents enables secure analysis of even sensitive content, opening up entirely new application areas.

At the same time, organizations gain maximum independence through the opening of the OpenAPI and MCP interfaces: external systems and data sources can now be connected independently and without support effort. The release is rounded off by technical support for Google Gemini 3 Pro, including the new image AI, ensuring access to the latest model generations.