Old knowledge management
Taxonomy first.
Define the categories. Write the articles. Tag everything. Verify the articles every six months. Watch nobody use it anyway. Repeat.
AI Knowledge Management
When a 10-year veteran leaves, what walks out the door?
Years of "why we do it this way", "who really signs off on that", "what we tried in 2019 that didn't work". None of it ever made it into a wiki. Knowledge management is broken because it asks the wrong people to do extra work.
The one-liner
AI knowledge management captures what your people already produce — tickets, contracts, transcripts, emails — and turns it into searchable, askable knowledge. No "knowledge articles" required.
Old KM asked humans to write down what they knew. They didn't. New KM reads what they do, and turns it into the same thing — automatically.
The cost of lost knowledge
What you lose when senior people leave.
Pull the org chart. Cross out everyone who's been there less than 18 months. Look at what's left.
The "why"
Why this clause was added. Why we don't take vendor X anymore. Why we sign off this way. None of it is in the wiki. All of it is in someone's head.
The "who"
Who really approves things. Who's the right person to escalate to. Who tried this in 2019. Org charts don't capture this; tribal knowledge does.
The "what we tried"
The dead-ends. The proposals that nearly happened. The reasons we don't do that anymore. Without it, every new hire repeats the same mistakes.
How passive capture works
The knowledge is already there. You just have to read it.
Your team produces knowledge every day. They write tickets. They reply to emails. They negotiate contracts. They run meetings. Certant reads it all.
Connect
Email, ticketing, contracts, meeting transcripts, the CRM. Certant reads them, in-place.
Extract
People, processes, products, policies, precedents. Every entity, every relationship.
Graph
Builds a live map: "this vendor is mentioned alongside this clause alongside this team alongside this decision."
Ask
"Who really signs off on these?" "Why was this clause added?" Answers cite the source — and tell you who to talk to.
Hand off
When someone leaves, what they knew didn't leave with them. The new hire asks Certant.
Old KM vs AI KM
From taxonomy to topology.
Old KM was a librarian. New KM is a map-maker. Same goal — find what you need — completely different approach.
AI knowledge management
Topology first.
Read what's actually produced. Map how it connects. Answer questions on demand. Re-read when documents change. No taxonomy committee.
Your knowledge management strategy shouldn't depend on people writing wiki pages.
FAQ
What heads of people and ops keep asking.
What is AI knowledge management?
AI knowledge management is the practice of capturing, organising and re-using organisational knowledge using AI — reading documents, tagging entities, mapping relationships, and answering questions with citations. The work humans used to do by hand, done continuously by the system.
How is this different from traditional knowledge management?
Traditional KM centres on taxonomy, ontology and human-authored "knowledge articles". AI KM centres on the documents and decisions your business already produces — contracts, tickets, transcripts, emails — 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 taxonomy 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. Old docs are not the enemy; un-flagged old docs are. The system tells you "this answer cites a 2018 policy — is it still current?" so humans can verify and supersede.
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 knowledge graph appear.