Services
Let us show you how we can contribute to your product literature publishing workflow.
| Workflow Step / How we can help | Use of Large Language Models / Artificial Intelligence 🤖 |
|---|---|
| 1. Legacy content conversion This is usually the most complex and challenging step in every project: We will examine your existing product literature (manuals, quick guides, brochures) and give you a quote for converting this legacy base to modern, web-based documents. Depending on the number and complexity of documents and the source formats, this may take anywhere from a few days to weeks. In general, PDF conversion is more expensive and time-consuming than working from open (editable) source formats such as Microsoft Word and Adobe InDesign. |
Use of AI Artificial intelligence / large language models can be used to structure content scraped from PDFs or other legacy formats. But at least for the next few years, human editing will be required to evaluate and post-edit these “AI-cleaned” documents. |
| 2. Technical writing While we do not employ technical writers, we can help you make your content web-ready and translation-ready. This includes formatting cleanup and making content translation-friendly. Making a document (set) translation-friendly usually involves sentence-level edits where we will remove ambiguity and passive voice, and fragments are converted into complete sentences. |
Use of AI Large language models can be used for making content more translation-friendly, but humans should evaluate and post-edit LLM output. |
| 3. Typesetting and structuring content Depending on the quality of the source documents, no or minor formatting may be required at this step. Plain, unformatted content, however, needs to be formatted / structured. We use a set of dedicated scripts and macros in this step. |
Use of AI Large language models can be used to detect document structures such as headings and lists and add the required Markdown tags. |
| 4. Adding metadata Metadata such as dates, product categories, and document types make documents more useful and allow us to fine-tune the publishing process as well. For example, metadata can be used to present or hide certain template sections. We use a set of dedicated scripts and macros in this step. We can also process prepared metadata from brands. |
Use of AI Large language models can be used to create metadata “seeds”; for example, keywords derived from a text. |
| 5. Translation In general, there are three options for translation: (1) We can have your content translated by professional human translators; (2) We can publish machine-translated content as such with a custom degree of editing (from “as is” to meticulous proofreading and post-editing), or (3) We can publish your content in English only, relying on machine translation engine support in modern browsers. |
Use of AI In all three models, AI is used: (1) Professional translators will use machine translation, translation memories (databases with previously translated content), and termbases to deliver solid translations. (2) Post-editing machine translation content is a common workflow for combining the best of both worlds (quick machine translation) and human expertise for ensuring solid results. (3) Modern browsers have access to machine translation engines, both as a built-in feature and using extensions. |
| 6. Publishing Finished documents are converted / “rendered” as HTML documents and optionally as PDFs. We can publish documents for you, or you can use our web interface for triggering the process. |
Use of AI No AI is used in this step. |
Further reading: “Markdown and Large Language Models: a perfect combination”
Investing in a modern documentation publishing format and workflow will lay a foundation for many years to come. We are ready to bring your brand’s manuals, quick guides, and FAQs into the 21st century.
↻ 2025-08-21