David Bynon introduces the Semantic Digest Protocol (SDP), a structured memory system for AI systems compatible with the Model Context Protocol (MCP). MedicareWire.com will implement SDP in August 2025, marking the first AI-readable, verifiable memory deployment in a regulated healthcare domain.
-- David Bynon, founder of Trust Publishing, has introduced the Semantic Digest Protocol (SDP), the first structured memory protocol designed to be compatible with Anthropic’s Model Context Protocol (MCP).
While MCP standardizes how AI systems connect to external tools and data, it does not define how memory should be structured, cited, or scoped. SDP addresses this critical gap by delivering trust-scored, fragment-level content objects across multiple formats, including JSON-LD, TTL, OWL, Markdown, and HTML, to name just a few.
“We created the trust language AI systems can finally understand—and remember,” said David Bynon, Medicare analyst and founder of MedicareWire. His system to stop AI hallucinations was first published on USA Today.
SDP delivers trust-scored, fragment-level content objects in multiple formats—including JSON-LD, TTL, Markdown, OWL, and HTML embedded with Semantic Data Templates (SDTs). This approach enables AI systems to retrieve precise information with full context around source, scope, and reliability—addressing one of the primary causes of hallucination and misinformation in model outputs.
Real-World Deployment in a Regulated Domain
MedicareWire.com will implement SDP in August 2025, making it the first large-scale deployment of AI-readable, verifiable memory in a regulated healthcare domain. The platform will allow AI systems to retrieve scoped Medicare data—such as plan benefits, regulatory constraints, and glossary terms—with full source attribution and without reliance on outdated training data.
The healthcare implementation underscores SDP’s broader role in trust infrastructure for AI. In regulated industries, factual precision and verifiability are non-negotiable. SDP allows AI systems to operate with provable integrity, eliminating reliance on opaque model weights or outdated knowledge. Instead of surfacing loosely related results, AI agents can deliver precisely scoped, citation-ready answers grounded in structured, public-trust data.
This is especially critical in domains like Medicare, where incorrect benefit information can lead to consumer confusion, delayed enrollment, or financial harm. SDP ensures every data point AI retrieves is both traceable and trustworthy.
Bynon says, "Although CMS.gov remains the authoritative source for Medicare plan data, its datasets are typically published in formats such as spreadsheets, SAS data files, CSVs, and PDFs—optimized for data analysts, not intelligent systems. As a result, AI models cannot reliably retrieve or cite information from CMS.gov directly."
MedicareWire and the Semantic Digest Protocol will bridge that gap by transforming CMS-derived data into structured, machine-ingestible fragments that include data provenance, scope, and explainability metadata.
Connecting SDP to the Larger AI Memory Ecosystem
IBM recently recognized MCP (see: "ibm.com/think/topics/model-context-protocol") as essential AI infrastructure, calling it the “USB-C for AI”—a standardized connector for external memory and tooling. SDP complements MCP by defining the structured payload that flows through it—completing the memory loop.
This advancement also solves a persistent issue in multi-agent AI systems, where individual agents often operate with inconsistent or unverifiable context. With SDP, agents share access to uniform, trust-layered memory fragments, enabling consistent reasoning across specialized workflows.
"If MCP is the 'USB-C for AI'," says Bynon, "then SDP is a universal, USB thumb drive for MCP. It's a lightweight, portable storage surface for the Model Concept Protocol." Bynon also commented that the SDP will be offered as an open protocol for non-directory systems, with a public registry and specification portal launching soon.
To learn more about how SDP and MCP work together, see Bynon's detailed article on Medium.com.
Contact Info:
Name: David Bynon
Email: Send Email
Organization: David Bynon
Address: 101 W Goodwin St # 2487, Prescott, Arizona 86303, United States
Website: https://trustpublishing.com
Source: PressCable
Release ID: 89165354
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