Start with work someone already does well.
Some of the most valuable expertise inside a company lives with a small number of people.
They know where to look. They notice things other people miss. They have learned which context matters and what a good result looks like.
LMTY can help turn work like that into a private AI Expert more of the team can use.
- 01
Tell us what happens today.
You do not need to design an agent for us.
Describe the work in plain English.
Tell us about the last real time it happened. Who got involved. What made it difficult. What happened when it went well or badly.
That gives us something real to diagnose.
- 02
Show us where the expertise lives.
A strong Expert candidate usually has a person or group who can explain how the work is actually done.
They may have a method they use without naming it. They may rely on years of examples. They may know which edge cases matter and which shortcuts are dangerous.
That judgment is part of the work.
- 03
Make the context available.
The job may depend on CRM data, calls, company documents, product data, market information, pricing, support conversations, analytics, or other sources.
We map what the work needs before deciding how the Expert should access it.
- 04
Define what good means.
An Expert needs a quality bar.
That can come from examples, human review, business outcomes, explicit standards, or a repeatable acceptance test.
The goal is to know whether the system performed the job, not whether the output sounded impressive.
A new job does not automatically become a new Expert.
- Sometimes the work belongs inside an Expert that already exists.
- Sometimes it suggests a new Skill Pack.
- Sometimes it genuinely needs its own domain and operating loop.
We start with the job and earn the architecture from there.