Machine Experience, make anything you publish readable by machines
Videos, podcasts, PDFs, images, web pages: make anything you publish readable by machines.
Structure for machines. Explicit for everyone. X-ray your website.
Machine Experience (MX) makes digital assets and documents readable by every machine that consumes them, so no machine has to guess.
The machine universe is expanding. AI agents, robots, autonomous vehicles, industrial systems, IoT devices, medical instruments, and classes of machine not yet invented all read the same documents.
Your website is a fraction of your content estate. Contracts, policy documents, product specifications, and technical reports never reach the web, but AI agents are reading them anyway, inferring what they can and guessing the rest. Being on the web and being machine-readable are not the same thing.
MX is the DNA a file carries when it leaves any system. It governs what survives extraction, so the next reader can answer the same questions the originator used to answer.
MX builds on what you already have. Schema.org and JSON-LD describe what entities mean, WCAG defines accessibility, Open Graph handles sharing. MX adds governance, provenance, lifecycle state, and agent affordances where those standards leave gaps, never duplicating what they already cover.
A provenance layer for machines
The web and the wider world of data files lack a provenance layer for machines. MX/REGINALD is built to be it.
The industry is preparing to use AI safely inside its walls. Nobody is preparing to be read well outside them. That is the gap, and four parts close it.
- MXis the contract.
- The Gatheringsets the standards.
- REGINALDdoes the signing.
- CogNovaMXoperates the service.
The EU AI Act is the first regulatory forcing function. Other jurisdictions are following.
Schema.org shows the gap in miniature. Structured data tells a machine what something is, but not whether to believe it; Google's deprecation of FAQ rich results is what happens when that gap gets gamed.
The agentic web is the technical and economic case. Machine adoption is exponential, today's web is hostile to it, and cogs replace expensive inference with cheap execution. That is the engine behind the framework, and it is being built now.
Consultancy
MX audits
Understand what AI agents see when they visit your site. Gap analysis and prioritized roadmap. PDF estate covered against the European Accessibility Act.
Mentoring
Ongoing advisory for teams implementing MX. Architecture guidance and hands-on support.
Examples
MX in practice. Real-world implementations across different industries and platforms.
New: Why an MX audit pays for itself. Three ways the work returns its cost: reduced inference cost across every reader, fewer hallucinated citations, and lower regulatory exposure under the EAA.
Compliance and trust
MX makes content machine-readable. REGINALD makes it machine-trustworthy. Together they meet the provenance and accessibility requirements emerging in the EU AI Act, the European Accessibility Act, and digital-records legislation across multiple jurisdictions.
REGINALD
The registry that makes MX-attested content verifiable. Cryptographic provenance, narrowly scoped: this is what the publisher published, unaltered.
Why the agentic era needs infrastructure
Public-sector and regulated-industry content estates need an infrastructure layer, not just intelligence. MX, COGS, and The Gathering provide it.
Ready to make your content estate work for AI agents? Get in touch or email info@cognovamx.com