The A.L.EX. method · knowledge that stays
When Alex leaves, the knowledge leaves too.
The A.L.EX. method makes sure it stays.
Your service memory draws on three sources. The A.L.EX. method takes care of the hardest one: what your experts know. It collects that knowledge in three levels, has it checked and brings it to every machine.
THREE LEVELS
Source 3 of 3: What your experts know
ONE MEMORY
AT EVERY MACHINE
PASSIVENO EXTRA EFFORT
Runs along on the job
Order · report · voice input
ACTIVE5 TO 10 MIN.
A short follow-up
After selected jobs, depending on your focus
DEEP1 TO 3 HRS.
Interview with the expert
CDM interview · video · diagnostic tree
Checked by an expert
memory VERIFIED · WITH SOURCE
At the machine
via QR code, no app, with source
CORE
In the work order
step by step on the job
CONNECT
In the assistant
asks back and coaches new technicians
COMPANION
What is learned on the job flows back
THREE LEVELS
Source 3 of 3: What your experts know
PASSIVENO EXTRA EFFORT
Runs along on the job
Order · report · voice input
ACTIVE5 TO 10 MIN.
A short follow-up
After selected jobs, depending on your focus
DEEP1 TO 3 HRS.
Interview with the expert
CDM interview · video · diagnostic tree
Checked by an expert
ONE MEMORY
memory VERIFIED · WITH SOURCE
AT EVERY MACHINE
At the machine
via QR code, no app, with source
CORE
In the work order
step by step on the job
CONNECT
In the assistant
asks back and coaches new technicians
COMPANION
What is learned on the job flows back
01
Smoothly in
Knowledge arises as a by-product of the work. At the machine and by voice, not at a desk.
02
Checked, not guessed
The validation loop filters out workarounds before the AI scales them.
03
Stays in the business
Available at the machine, in the app and through the AI. Even when Alex leaves.
Extract → Validate → Scale
First extract, then validate, then scale.
The knowledge journey
From the head into the platform.
The graphic above shows how knowledge comes in and goes back out. What sits behind it, we show here in excerpts.
Scientific foundation
Tacit Knowledge (Polanyi)
Masters know more than they can say.
SECI model (Nonaka/Takeuchi)
Tacit knowledge only becomes valuable once it is shared.
Recognition-Primed Decision (Klein)
Experienced technicians decide before they think it through.
Extraction without validation scales errors.
Between capturing and using sits a step that many wiki and documentation tools simply skip. With A.L.EX., that is exactly where the real work happens.
The validation loop
Knowledge that is no longer checked goes out of date. Even if it was captured well once. A.L.EX. closes this loop instead of leaving it open after extraction.
Knowledge maturity
- Tied to a person
- Documented
- Validated
- Scalable
intuAid positions itself at the transition from validated to scalable. Most businesses today stand just before it.
How an experienced technician thinks before deciding, made visible.
The diagnostic tree sits behind the CDM interview from the graphic above. What it shows in detail, we discuss in conversation.
The question is not whether your knowledge leaves. The question is whether it stays.
Next step
We support you through the change.
From the first analysis to ongoing knowledge upkeep. Talk to us about your business.