Ontology Builder
A composable definition block — your firm's vocabulary, relationships, and rules in one portable model, interoperable with your existing stack.
Your systems hold the facts. Your people hold the meaning.
Your trust accounting platform knows that Account 4471 has a balance and a tax ID. It does not know that the account sits inside a revocable trust, that Jane Smith is a contingent beneficiary rather than a current one, or that a distribution above a threshold needs a second approval. That knowledge lives in operations manuals, conversion notes, and the heads of the three people who have been there longest.
An ontology writes it down in a form software can act on. Think of it as a map of the nouns and verbs of your firm — what things are, how they connect, and what rules apply. Jane Smith is a Beneficiary of Trust 88-A. Trust 88-A holds Account 4471. Two statements, and every system you own can answer questions nobody coded for in advance.
- Plain-language modeling Describe entities, roles, and relationships in business terms. No query language, no schema files, no data engineering ticket.
- Rules as first-class objects Fee tiers, distribution thresholds, fiduciary approvals, and eligibility tests captured as governed logic rather than tribal knowledge.
- Grounding for AI Give agents and natural-language tools your definitions instead of their assumptions. The difference between an assistant that sounds right and one that is right.
- Vendor-neutral by construction The model belongs to you, not to your platform. Export it, version it, and carry it through any conversion.
The asset that survives your next conversion
Every migration re-litigates the same questions: what counts as an account, which fee schedule governs it, who is entitled to what. Firms answer them from scratch each time because the answers were never written down anywhere except inside the system being replaced.
Ontology Builder makes that layer an owned asset. The ontology is the blueprint; our Knowledge Graph is the building raised from it. It pairs directly with our Parallel-Run method, where the model becomes the specification both the legacy and replacement systems are tested against, and it feeds Knowledge Graph, Agent Studio, and the Natural Language Interface from a single source of truth.
Got-Data Inc. brings Neo4j-certified graph engineering and three decades inside trust accounting platforms to a domain where the definitions are genuinely hard — fiduciary roles, entity hierarchies, and fee mechanics that no generic modeling tool anticipates.
We are currently accepting early access partners who want to shape the product against real institutional data models and use cases.