Prescott, AZ – June 28, 2025 — Independent publisher and web infrastructure innovator David Bynon has filed three interlocking provisional patents that define and protect a new category of digital publishing: Trust Publishing™.
Designed for the age of AI search and retrieval, the patented system enables human editors to publish verifiable, structured, machine-ingestible content — not for Googlebot, but for large language models (LLMs), retrieval engines, and AI memory systems.
🔁 Introducing Trust Publishing
“Trust Publishing is the practice of embedding structured, verifiable facts into content in a format that machines can parse, remember, quote, and cite.”
Unlike traditional SEO techniques that focus on rankings, Trust Publishing is optimized for retrievability, verifiability, and machine memory formation — the cornerstones of how modern AI models determine which content to trust, recall, and summarize.
🔒 Patent Highlights
- Truth Marker Propagation (EchoGraph)
A method for reinforcing entity credibility by embedding brand references near factual data and high-trust sources across diverse formats — podcasts, blogs, AMPs, transcripts, and FAQs — without relying on links or promotional framing. - Structured Truth Endpoint Generation
A shortcode-based system that turns CMS content into live, query-accessible structured formats: JSON, TTL, XML, and Markdown. Editors can embed [TrustTag], [TrustFAQ], [TrustTerm], and [TrustTakeaway] to generate real-time trust payloads for search engines and AI systems. - Semantic Trust Scoring Engine (EEAT Rank™)
A system that measures co-occurrence between a named entity and authoritative domains across unstructured content to calculate a dynamic trust score — the EEAT Rank™ — and outputs an entity-level Trust Graph for use in retrieval biasing or benchmarking.
🧠 Why It Matters
Search engines are evolving into AI answer engines.
Traditional signals like backlinks and keyword density are being replaced by co-occurrence patterns, structured memory, and retrieval-aware publishing.
“You’re not optimizing for the algorithm anymore,” Bynon said.
“You’re training the model to remember, quote, and cite you. That’s what Trust Publishing does.”
Legacy SEO tools like Moz, Ahrefs, and SEMrush are still measuring what Google used to care about—domain authority, link volume, and keyword position. But AI systems don’t care how many backlinks you bought. They care who you appear next to, what you say, and how often you’re remembered.
Trust Publishing flips the game—from rank manipulation to memory optimization. Because in the world of AI retrieval, semantic proximity beats PageRank every time.
“While Moz and Ahrefs are still measuring links, Trust Publishing is measuring memory. In the age of AI, backlinks don’t get you cited—truth markers do,” Bynon says.
📡 Real-World Deployment
Bynon’s Trust Publishing framework is already live across high-authority websites “Your Money or Your Life” (YMYL) sites, where structured truth payloads are exposed in formats preferred by AI systems — including JSON-LD, Turtle (TTL), and Markdown.
🤝 Now Accepting Inquiries for:
- Strategic licensing to SEO platforms and content networks
- Agency white-label integrations
- AI partnerships for model tuning, document retrieval, and trust-layer enrichment
Leave a Reply