No-Code Knowledge Bots
Build a question-answering bot over your team's docs without code, test it against real questions, and keep its knowledge current.
Every team has a few people who get asked the same questions all day. "What's our refund window for annual plans?" "Who approves an SLA exception?" "Where's the escalation checklist?" The answers are written down somewhere, in a wiki page, a policy PDF, or a doc from two reorganizations ago. Nobody can find them, so they ask a person.
A knowledge bot answers those questions from your documents, and you can build one without code in an afternoon. Building one people trust takes a little longer, because knowledge bots fail in a particularly convincing way: a fluent, confident answer from the wrong document, or from no document at all. In this lesson you'll pick a home for your bot, prepare the documents, write instructions that keep answers grounded, test it against real questions, and set up the habits that keep it current.
How a no-code knowledge bot finds answers
When someone asks your bot a question, the tool has to get the right parts of your documents in front of the model. It does this in one of two ways:
- Read everything. If your files are small enough, the tool includes all of them in the model's context with every question. This is simple and works well for a handful of documents.
- Search, then answer. For larger collections, the tool first searches your documents for passages related to the question, then gives only those passages to the model. This is called retrieval-augmented generation, or RAG. Many tools switch to this automatically once your files pass a size limit, without telling you.
This matters because it explains most failures. With retrieval, the model can only answer from the passages the search found. If the question uses different words than the document ("cancel" versus "terminate"), or the answer is spread across five documents, the search may miss it, and the model either says it doesn't know or, worse, answers from general knowledge. Developers build and tune this machinery in Module 5; in no-code tools it's hidden, so your levers are the documents, the instructions, and the testing.