THE PROBLEM
What goes wrong without schema clarity
When entities and schema are inconsistent, AI platforms misread your business content, and visibility drops.
Wrong Entity Matching
Your brand gets confused with similarly named companies, locations, or services.
Low AI Citation Visibility
AI assistants skip your site because structure and trust signals are incomplete.
Fragmented Site Signals
Schema, content, and internal linking tell different stories across your site.
HOW IT WORKS
Three steps to visibility
Submit Your Site
Enter your URL and we crawl your schema, entities, metadata, and linking structure.
Get Your Audit
Receive a detailed report with severity-ranked issues and exact fix specifications.
Implement & Grow
Follow the 30/60/90-day roadmap β quick wins first, then deeper improvements.
WHAT YOU GET
Everything in your VISEON audit
A complete AI discoverability toolkit β from diagnosis to implementation plan.
Issue Matrix
Prioritized schema, entity, and structure issues grouped by severity and business impact.
Fix Specifications
Clear implementation guidance for devs or content teams, with exactly where to apply each fix.
30/60/90 Roadmap
Quick wins first, then deeper improvements for durable AI discoverability gains.
Schema Audit
Organization, LocalBusiness, and service schema completeness checks.
Entity Consistency
Entity alignment across pages, metadata, and knowledge graph signals.
Linking Analysis
Internal linking patterns that support AI understanding and citation paths.
PROOF FROM REAL TEAMS
Businesses trust VISEON to fix their AI visibility
“Thank you for helping us fix our Schema for AI Semantic Search. Since adding our Schema catalog knowledge graph catalog we’re now winning business and appearing alongside bigger companies in search.”
“After working with VISEON, The Lovely Barns is finally showing up properly online, and AI now gives clear, detailed answers about our Algarve barns instead of confusing us with other properties.”
“After partnering with VISEON, ATP Construction LLC has received much more attention than it used to. We used to get confused with a company in Idaho with the same name, but now, local residents find us easily.”
FAQ
Frequently asked questions
Semantic MDM (Semantic Master Data Management) applies the disciplines of enterprise MDM β golden records, entity survivorship, schema stewardship, and change governance β to the outward-facing semantic layer of your website.
Where traditional MDM governs master data inside the enterprise (customers, products, suppliers, employees), Semantic MDM governs the machine-readable entity definitions that AI agents, search engines, and agentic commerce systems encounter at the AI-facing boundary.
VISEON:Discover runs this process in three stages: Audit β crawl and validate every entity definition against Schema.org, identifying duplicates, conflicts, and semantic misalignments. Enrich β resolve conflicts and establish a single Golden Entity Record per entity. Publish β compile a Semantic MDM DataCatalog: a machine-readable, AI-traversable index of all validated entity records.
The result is a website whose meaning is as governed as its data.
The initial Audit is delivered within 7β14 business days, depending on the size and complexity of your domain.
The audit covers every entity definition across your site β validating @id integrity, identifying duplicate or conflicting records, surfacing semantic misalignments, and scoring your knowledge graph against Schema.org. You receive a prioritised issue matrix with exact fix specifications, not a generic report.
Enrichment and data catalog publication follow as subsequent stages, each building directly on the audit output.
For the Enrich stage, yes β resolving entity conflicts, establishing your digital catalogue’s Golden Entity Records, and implementing schema corrections requires technical resource. This is a deliberate, expert-led process: each entity definition is reviewed and enriched as part of the process against your operational reality before it is published to the catalog.
VISEON provides implementation-ready specifications β exact @id corrections, entity definitions, and structured data snippets β that your development team can apply directly. If you do not have internal resource available, VISEON can implement on your behalf.
Yes. VISEON:Discover is infrastructure-agnostic at the output layer. The Semantic MDM Data Catalogue is published as standard JSON-LD and is compatible with any CMS, e-commerce platform, or enterprise system.
For WordPress sites using Yoast, Rank Math, or custom schema implementations, VISEON audits and validates the schema those plugins produce β and enriches it where it falls short.
For enterprise deployments, VISEON integrates with your existing BOAT infrastructure (Business Orchestration and Automation Technologies – Gartner) to govern and maintain the semantic layer over time. Where BOAT integration is in place, the catalogue can be kept current with source system changes and published in alignment with the Open Semantic Interchange (OSI) standard β enabling interoperability with AI agents, BI platforms, and analytics tools across any compliant platform.
Yes. You can engage VISEON for Audit only, or extend to full Semantic MDM delivery β covering Audit, Enrich, Govern, Maintain, and Publish.
The Maintain service provides ongoing schema stewardship: keeping your digital catalogue’s Golden Entity Records aligned with operational reality as your products, services, and organisation evolve. This is the managed service equivalent of what your CDO does for internal master data β applied to the AI-facing semantic boundary.
Contact us to discuss which engagement model fits your requirements.
Ready to get discovered by AI?
Join teams from your industry that use VISEON:Discover to fix schema, adopting semantic MDM, to resolve entity confusion, and build durable AI visibility.




