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What walks out when they leave

Why you do it this way, who really signs off, what you tried in 2019. None of it ever made it into a wiki.

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Captured from the work your team already does. Every answer cites its source.

Example
What leaves when a long-serving colleague does A long-serving colleague, about to leave, holds five pieces of knowledge: a vendor's late deliveries, why a contract clause was added, who signs off on spend, a vendor policy, and a rule about the data lake. A catch-net labelled "Certant reads it as it happens" sits below, connected to each piece by a dashed line. A long-serving colleague leaves on Friday "that vendor is always 3 weeks late" "clause 4.2 was added after the 2019 incident" "Jen in HR signs off on anything over $5k" "we don't take SOC2 type 1 vendors anymore" "the data lake is read-only unless you ping ops first" Certant reads it as it happens from tickets · emails · meeting notes · contracts

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In one sentence

AI knowledge management reads the tickets, contracts, transcripts and emails your people already produce, and turns them into searchable, askable knowledge. No knowledge articles required.

Old knowledge management asked people to write down what they knew. They didn't. This reads what they already produce instead.

The cost of lost knowledge

What you lose when senior people leave

Cross the recent starters off your org chart and look at what is left.

The why never makes it into the wiki: why this clause was added, why you don't take vendor X anymore, why you sign off this way. All of it is in someone's head.
The who never shows up on an org chart: who really approves things, who's the right person to escalate to, who tried this in 2019.
What you tried is easy to forget: the dead ends, the proposals that nearly happened, the reasons you don't do that anymore. Without it, every new hire repeats the same mistakes.
How passive capture works

The knowledge is already written down

Your team produces knowledge every day in tickets, emails, contracts and meeting notes. Certant reads all of it.

  1. Connect Email, ticketing, contracts, meeting transcripts, the CRM. Certant reads them in place.
  2. Extract People, processes, products, policies, precedents. Every entity, every relationship.
  3. Map Builds a live map: this vendor sits alongside this clause, this team and this decision.
  4. Ask "Who really signs off on these?" "Why was this clause added?" Answers cite the source, and tell you who to talk to.
  5. Hand off When someone leaves, what they knew didn't leave with them. The new hire asks Certant.
Old KM vs AI KM

What changes about the job

The old job was librarian. The new job is closer to map-maker. Same goal, different method.

Old knowledge management

Categories first

Define the categories. Write the articles. Tag everything. Re-verify it all twice a year. Watch nobody use it.

AI knowledge management

Connections first

Read what your team actually produces, map how it connects, and answer questions from it. Re-read when the documents change. No committee required.

FAQ

What heads of people and ops ask

The questions that come up before anyone signs off.

What is AI knowledge management?

AI knowledge management is the practice of capturing, organising and re-using organisational knowledge using AI: reading documents, picking out the people, policies and decisions in them, mapping how they connect, and answering questions with citations. The work someone used to do by hand, done continuously.

How is this different from traditional knowledge management?

Traditional knowledge management centres on categories, structure and hand-written articles. AI KM centres on the contracts, tickets, transcripts and emails your business already produces, and uses AI to build the structure. The work moves from authoring to asking.

How do we capture tribal knowledge before someone leaves?

Stop trying to capture it as articles. Capture it in flight. Certant reads the tickets, emails, meeting transcripts and contract notes your senior people produce in their normal work, and turns it into searchable knowledge automatically.

Does this replace our KM team?

It changes their job. Less time on categorising and verifying articles; more time on designing playbooks, building agents and steering what gets escalated to people.

What about old, stale documents in our archive?

Certant timestamps every source and surfaces freshness on every answer. An old document is fine. An old document nobody has flagged is the problem. The system flags it: this answer cites a 2018 policy. Is it still current? A person verifies and supersedes it.

How does this play with our existing KM system?

It reads it. Most teams add Certant on top of Confluence, SharePoint, ServiceNow KB or Salesforce Knowledge. The articles you already have become one of many sources; the gaps become one of many places to ask.

Capture what they know before they leave

Connect your tickets, contracts and transcripts. Watch the map of how they connect appear.

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The point of this page

Your knowledge management shouldn't depend on people writing wiki pages.