Knowledge Chat: Stop Searching. Start Asking.

You probably know the feeling: somewhere in a quality manual, an EMVI document, or an old project folder is exactly the answer you need. You know it exists, but you just can’t remember where to find it.

So the search begins. You use Ctrl+F in one file, scroll through another, and message a colleague in the hope they still know. Ten minutes later, you may have your answer, or you give up and continue based on assumptions.

Knowledge Chat breaks that pattern. Instead of searching manually, you simply ask your question in plain language and get an immediate answer from your own documents. No scattered keywords, no endless folder structures, no guesswork. Just a smart digital companion, developed for systems engineering.

01 | How it works: question led and source grounded

Knowledge Chat is a chat interface with direct access to your own documents, including your quality system, EMVI files, project files, and contract documents. You ask a question in plain language. The system searches your connected cloud storage, such as SharePoint or OneDrive, and generates an answer based on the current content of those files.

The result is an answer with precise source references, so you can verify exactly where the information comes from. You can also easily import files such as PDFs and Excel documents, and export results to a spreadsheet for further use in your project.

02 | The technical difference: Retrieval-Augmented Generation

A standard language model such as ChatGPT generates answers based on general training data. Useful for broad questions, but less suitable when you want to know what your quality manual specifically says about verification methods, or which agreements are laid down in a particular project document.

Knowledge Chat uses RAG technology, or Retrieval-Augmented Generation. That is the fundamental technical difference. The system first goes through the retrieval phase, in which it pulls the relevant information from your own documents. Only then does the generation phase follow, in which the language model formulates an answer based on that specific information. As a result, the answer is grounded in your own sources, and thanks to the source references, you can verify that foundation yourself. AI identifies and substantiates; you review and decide.

03 | Fits seamlessly into your existing workflow

You do not need to learn anything new to get started. Knowledge Chat connects directly to your documents in the cloud, such as SharePoint or OneDrive, so it always works with the most up to date version of your files. No new system and no new way of working, just a much faster route to the answer you were already looking for.

Three ways teams use Knowledge Chat

Documentation and planning

• Create a technical management plan using existing project documentation as a foundation.

• Develop a verification and validation master plan without starting from a blank page.

Verification and validation

• Quickly check how a specific requirement should be verified without going back to the original contract document.

• Check whether a requirement has already been met by searching the available supporting evidence.

• Link risks to requirements by extracting related risks from documents.

Structure and setup

• Create an initial outline for a systems breakdown structure, or SBS.

• Generate a high level work breakdown structure, or WBS, in one go after analysing the documents.

The common thread is clear: these are tasks that would normally take hours of manually combing through documents, and that can now begin with a single question.

Practical example: a three level systems breakdown structure

In a recent project, a systems engineer asked Knowledge Chat to structure the system into three levels: main system, systems, and subsystems. Before generating the structure, the chat first clarified the assumption about which components should be treated as external and which as internal.

Knowledge Chat then generated a table for each level. For every system and subsystem, it provided a rationale that could be traced directly back to the source text in the project documents. The result was not just a loose list, but a structured output in which every answer remained traceable to the original source. The engineer could immediately export the result to a spreadsheet for further development with the project team.

04 | From searching to steering: the value for your project

The Knowledge Chat changes the way systems engineers and project managers work with project information. Instead of relying on assumptions or spending valuable time piecing together answers from different files, you work from what is actually documented. That creates a stronger foundation for day to day decisions, whether you are shaping plans, validating requirements, or aligning teams around the next step.

The time you save on searching can be invested where it matters most: analysing trade offs, managing risks, and making well founded decisions. That does not just improve speed. It also increases confidence across the project, because answers are grounded in traceable source material rather than memory or interpretation alone. In complex projects across construction, infrastructure, and energy, that combination of speed and certainty makes a real difference.

Knowledge Chat also helps teams stay consistent. When everyone can access the same project knowledge in the same way, it becomes easier to work from a shared understanding of requirements, responsibilities, and evidence. That reduces rework, prevents avoidable misunderstandings, and supports better collaboration across disciplines.

Want to see how SE Knowledge Chat works with your own documents? Book a personal demo at www.basewise.ai and discover what it could mean for your project team.