The answer exists. It is in a chat thread from March.
Every team has this problem and almost none of them have a documentation problem. The answers were written; they were written in the wrong place, once, to one person.
Search here matches meaning rather than words, so “can I send it back after a month” finds the refunds policy even though the policy never uses the word month. What it returns is the article — not a generated summary that might be right.
Ranked by meaningBuilt on an embedding index that is rebuilt as articles change, not on a keyword table somebody has to maintain.
The citation is the answerYou are sent to the paragraph. A knowledge base that paraphrases its own articles has invented a second source of truth.
Scoped to who is askingAn internal article does not surface for a customer, and access is evaluated at retrieval rather than filtered afterwards.
Writing it
The reason knowledge bases die is that writing in them is a chore.
So the work here is in the shortest path from an answer someone just typed to an article that exists.
Turn a chat answer into an article
Somebody answers the refund question in Piskes Chat for the fifth time. One action turns that reply into a draft article, with the question as the title and the answer as the body, waiting for a two-minute edit. That is the whole loop, and it is the only one that has ever worked.
Seven templates
Policy, how-to, troubleshooting, definition, checklist, decision record, FAQ. A shape to fall into beats a blank page.
Articles that admit their age
Every article carries when it was last confirmed true, and stale ones are listed for review rather than quietly rotting.
Anyone can suggest an edit
A suggestion goes to the owner, so being wrong in public is not the cost of fixing a typo.
The same index, three places
Written once, answered everywhere.
01
A person searches it
The knowledge base itself, internal or public, with the access rules applied per reader.
02
The chat widget suggests from it
Piskes Chat proposes articles as your agent types, so the answer sent is the answer you already wrote.
03
An agent retrieves from it
Piskes Agents ground on the same index, which is why they can say something true about your business rather than something plausible.
What the first month looks like
Honestly, week by week.
From teams starting from nothing
W1
Twelve articles
All of them promoted from chat threads. None of them written from scratch, because nobody writes documentation from scratch.
W2
The first search that works
Somebody finds an answer without asking. This is the week people start believing in it.
W3
The widget starts suggesting
Support replies get faster because the article is offered rather than remembered.
W4
The first stale flag
An article passes its review date and is listed. This is the mechanism that decides whether you have a knowledge base in a year.
7Article templates
1Index behind everything
2 minChat reply to draft article
∞Readers per workspace
Pricing
By articles, not by reader.
Charging per reader on a knowledge base is charging you to let people find the answer, which defeats the purpose you bought it for.
Prices in USD, billed monthly. A public space costs the same as a private one.
Questions
From teams that have abandoned one of these before.
How is this different from a wiki?
A wiki has no retrieval and no review dates, so it becomes an archive of things that used to be true. The two mechanisms on this page — promote from chat, flag when stale — are the entire difference.
Can we publish some of it to customers?
A space can be public, on your own domain on Business. Access is per space, and an internal article never surfaces in a public search.
What happens to search when an article changes?
The index is rebuilt for that article on save. There is no nightly job to wait for and no state where the search result and the article disagree.
Can we import what we have?
Markdown and HTML, keeping the folder structure as spaces. Confluence and Notion exports both land in that shape.
Start with the question your team answers most.
Not with a structure, not with a template library, and not with a documentation plan. One question, one article, and the loop that turns the sixth answer into the seventh reader’s search result.