Last year, artificial intelligence reached a level of maturity where it was ready to use. Together with content delivery, AI is probably the hottest trend in technical communication right now. But where are we at in terms of actual solutions for everyday use? A lot of people are talking about the relevance of both these topics at the moment. But many technical writing teams don’t have the facts that clarify how these two trends can converge. So we want to use this blog post to show you how Quanos connects these two issues and gives (not just) technical writing teams the edge in the process.
Let’s start by taking a look at these two topics from the perspective of digitalization. One of the key concepts here is the digital twin, which digitally maps a host of product aspects ranging from the idea, to development, through the finished end result. This digital image can then be used to model, monitor, and ultimately control the product as well. The digital twin also comprises all the information relating to the product. This includes various sets of instructions for assembly, maintenance, and operation, for example, as well as data and measured values.
As things currently stand, this information is dispersed across many different systems and platforms in a given company, such as the CCMS in technical writing, ECAD systems in product development, or the enterprise resource planning system. So the first step for the digital twin is making this data compatible with each other. Once this is done, it needs to be linked up, integrated on a common platform, and then made available to different target groups (e.g., dealers, customers, service technicians, technical support, etc.). Quanos InfoTwin takes on this role by serving as the central platform for content delivery.
But how does artificial intelligence come into play in this process? As we mentioned above, making existing information compatible with each other is one of the steps in introducing content delivery. This isn’t always completely straightforward with technical documents in particular, as these often come in formats that aren’t easy to integrate into the digital flow of information. Some documents also contain a variety of information meant for different purposes. But this information has to be merged with data from other sources in the digital twin.
This is where AI gives you a huge advantage by using powerful statistical methods to organize the chaos in the existing documents. For example, it can identify a document’s language based on characteristic combinations of letters. It applies rule-based systems to determine the type of document, product groups described, and processed components. AI can detect page sections and self-contained units in PDFs and ensure that the content can be read in the text flow. And it’s capable of combining metadata and generating titles automatically, for example.
Given these capabilities, AI can play an important role in preparing information from technical writing departments for content delivery. To make this as simple as possible, the content management system, artificial intelligence, and content delivery platform should be closely linked with one another.
The tandem between InfoTwin and plusmeta, the powerful Quanos AI, is just this type of solution. Information can be easily transferred here using drag and drop. A seamless connection ensures the AI keeps pace with InfoTwin data modeling at all times. This makes it easy to segment data, detect metadata, and use them for InfoTwin. In other words, AI really gets content delivery moving.