A clever prompt is not a method. Before DeltaVault’s AI proposes a single entity, relationship, or definition, something has to tell it what your business means in your own words. That means the customer your team argues about in meetings, not the textbook one. We made that case in meaning before machinery.

So every AI feature in DeltaVault runs the same five-step loop: set the context, bring in the content, describe the outcome, review the proposal, then refine and approve. This how we use AI series walks that loop. It starts where the quality of everything downstream gets decided. That means it starts with context.

Watch this in action:

Context is a setting, not a sentence

In most tools, business context for AI is whatever you remembered to paste into the chat box. DeltaVault treats it as a governed setting instead. It’s a matter of data governance, not chat history, and you author it once under Settings and Conventions through a guided wizard. You start with your business categories, the named kinds of thing that every entity in your model gets tagged with: Customer, Order, Location, and so on.

You’re not inventing them from scratch. First you pick a starting approach. Ensemble Logical Modeling works from five broad archetype families, while Nine-Pillar spreads roles, offerings, agreements, and reference data across ten categories. Then you pick your industry, anywhere from regulated finance to retail and consumer goods, and the archetype names and AI guidance re-skin to match. DeltaVault ships a curated library, and every entry arrives with a starting definition you can adopt and adjust. There’s also a catch-all lane, a category for anything the others don’t cover, so nothing is ever left unclassifiable.

Each category then carries three attributes:

  • A type: is this an Event, something that happens like an Order, or a Concept, something that simply is like a Customer?
  • A question: who, what, where, when, why, or how?
  • An AI context: a short note, in your own words, saying what the category means to your organization.

Spend real time on that last field. The modeling and glossary skills read it every time they analyze your input.

Boilerplate is a starting point, not an answer

The library definitions arrive deliberately generic, and leaving them that way is the surest way to waste this step. So what’s the real work? It’s replacing them with your language: what your organization means by a person, whether a household counts as a concept in its own right, the distinctions your team already argues about in review. If you maintain a business ontology, it lands here.

The AI will even help you write its own instructions. Every context field supports drafting in place, so ask it to sharpen your wording, compare the suggestion against your original word by word, then apply or discard. Notice the shape of that interaction. Even while you’re configuring the AI, nothing changes without your review. The same loop holds at every scale.

Why does saved business context for AI lift every skill?

Once saved, your categories stop being a settings page. They become the frame every modeling skill works inside. Entity recommendations, relationship suggestions, and the modeling workshop’s discovery pass all read them, including each category’s type, its question, and the guidance text you wrote. Model review goes further. It judges every entity’s category assignment against your definitions instead of a generic taxonomy. And the data governance check cross-references a knowledge document against those same categories, so you can see which ones the document covers and where the gaps sit.

So this step deserves real time. An afternoon spent sharpening definitions is the cheapest AI improvement you’ll ever make. It lifts every proposal, every recommendation, and every review that follows, and you got there without touching a prompt. A vague frame gives you plausible answers about somebody else’s business. A sharp frame gives you proposals that already speak your language.

  1. Open Settings, choose Conventions, and define your categories.
  2. Meet us at the next post, Give AI content, not more prompts, where your own documents come in.