Trust Stack™ > AI Ontology & Claims Governance
Stop Model Confusion at the Source
LLMs index claims about entities. We architect your ontology, controlled vocabulary, and verified claim triples—with citations, statuses, and timestamps—so models don’t invent facts.
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Govern Your Facts, Win Your Mentions
Turn your story into an asset, not a rumor mill. We build your domain ontology, claims registry, and change controls so LLMs see one canonical truth.
Establish a Single Source of Truth for Your Company
A consistent, authoritative vocabulary keeps LLMs from splintering your brand into multiple versions of reality. Increase your authority by giving every LLM the same unambiguous reference data.
An Audit Trail that LLMs can Trust & Point To
By recording each fact with provenance, status, and timestamps, you give AI (and humans) a single, authoritative source to reference, eliminating guesswork and reducing the risk of fabricated details.
Build Credibility by Keeping Your Facts in Sync
Without clear version control, outdated or conflicting data can linger in LLMs indefinitely. Let’s ensure that every AI system sees the latest, most accurate information, while preserving a transparent record of what changed and when.
Eliminate Confusion Before it Erodes Your Authority
When LLMs can’t tell you apart from someone else, your authority erodes. Ensure every mention points to the right entity and protect your brand from mistaken identity and misattributed facts.
Make Your Truth Discoverable to the LLMs Your Audience Trusts
If your facts aren’t published in an authoritative, crawlable format, LLMs will source them elsewhere—or make them up. Skp the headache and give models a direct pipeline to verified data they can trust and cite.
How We Turn Knowledge Chaos into a Governed Source of Truth
We design, govern, and publish your entire knowledge layer—ontology, claims, version history, disambiguations, and authoritative storage—so LLMs see one clear, consistent reality.
🙊 Domain Ontology & Controlled Vocabulary
We create Canonical IDs for Organization, People, Products, Services, Events; agreed names, aliases, disambiguations. The result: fewer hallucinations, cleaner citations, stronger brand authority.
📔 Claims Registry
We build a structured ledger of “fact triples” (entity → predicate → object) with citations, status (draft/verified/retired), and timestamps. This eliminates guesswork and reduces the risk of fabricated details.s.
🩷 Authoritative Storage
We create a public, crawlable “/knowledge” or docs space exposing the ontology and key claims as JSON/CSV (and mirrored in JSON-LD).
🪪 Ambiguity & Collision Handling
Disambiguation pages, negative assertions, and duplicate collapses ensure every mention points to the right entity—protecting your brand from misattributed facts.
🛜 Change Management & Versioning
Semantic versioning, dateModified tags, and human-readable changelogs ensure every model sees the latest, most accurate information.
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Ontology & Claims Governance FAQs
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It’s Layer 0 of Trust Stack™: we design, govern, and publish your knowledge layer—ontology, claims, version history, disambiguations, and authoritative storage—so LLMs see one clear, consistent reality and stop inventing facts.
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A consistent, authoritative vocabulary prevents models from splintering your brand into conflicting versions. Canonical IDs, agreed names/aliases, and disambiguations give every LLM the same unambiguous reference data, boosting authority and reducing hallucinations.
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We maintain a structured ledger of fact triples (entity → predicate → object) with citations, status (draft/verified/retired), and timestamps—creating a single, citable record that eliminates guesswork and reduces fabricated details.
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Through semantic versioning, explicit dateModified, and human‑readable changelogs, so every model sees the latest, most accurate information while preserving a transparent audit trail of what changed and when.
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We implement disambiguation pages, negative assertions (e.g., “we are not X”), and duplicate collapses/redirects so every mention maps to the right entity—protecting authority and preventing misattributed facts.
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In a public, crawlable /knowledge (or docs) space that exposes ontology and key claims as JSON/CSV and mirrors them in JSON‑LD—giving models a direct pipeline to verified, citable data.
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Fewer hallucinations, cleaner citations, stronger brand authority, and one canonical truth that the rest of Trust Stack™ builds on—turning your story into an asset instead of a rumor mill.
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