Guide
Why a general AI model does not know how your company works
A general model learned from broad public text. It has not seen your policies, product rules, or past decisions, so it answers in general terms. A company adapter is a layer trained on material you approve, so the model can work in your terms.
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What a general model knows
A general model writes fluently about insurance, lending, or healthcare in general terms. It has not seen your policy wordings, your product rules, or the reasons behind past decisions.
So it answers the question as asked, not as your company would settle it. It cannot know which of your internal rules applies, and it uses your terminology only if someone supplies it. Pasting a policy into a prompt helps with that one question. It does not teach the model your company.
The usual workarounds
Teams often paste material into each prompt. That works for one task, but someone has to repeat it every time, and sensitive material ends up in places your reviewers did not plan for.
The other route is a custom training project. Those are often hard to review afterward, because nobody can say exactly which material shaped the result.
What a company adapter changes
An adapter is a smaller set of model weights trained on top of a base model. It changes how the model behaves without retraining the base.
Gpodz Compute is designed to train a company adapter on material your company approves: policies, product documentation, procedures, and terminology. One company adapter serves every team, so they share the same grounding. Role adapters then sit on top for individual functions.
By design, your material goes into your adapters, not into the base model that every customer shares.
What it does not change
The model can still be wrong. An adapter does not make it a system of record, and it does not remove the need for people to check the work. We publish no accuracy figures and make no claim about results.
This is also a design today. Gpodz Compute is pre-launch, and no customer deployment is in production.
How you can tell what shaped it
Your team selects the material. Each trained adapter is stored as a new version. Your reviewers test it on examples you choose, and it is activated only when you approve it. If a later version falls short, the previous version is designed to be restored.
That gives a reviewer something concrete to ask about: which material, which version, approved by whom.
Questions on this topic
Is a company adapter the same as training a new model?
No. The base model is not changed. The adapter is a separate, smaller layer trained on your approved material and stored as its own version.
Does a company model replace human review?
No. The model drafts and answers. People stay responsible for decisions, and your reviewers test each adapter version before it is used.
Is this available today?
This site describes the product design. Gpodz Compute is pre-launch. Which layers are available to your organization, and when, is confirmed in writing during scoping.
Talk through your own material.
Tell us which policies and rules a model would need to know, and who would approve them.