With #trstd <protocol>, verifiable trust becomes machine‑readable.
#trstd <protocol> enables AI agents to present verifiable identity, operator, intent and relevant mandates, while Brands provide verifiable identity, trust signals and access terms, and return policy decisions that define what agents are permitted to do.
With AI now the primary gateway, agent traffic is flooding the web.
With that scale comes a growing number of rogue agents scraping data, probing systems or automating abuse. Brands face a costly dilemma: allow agent traffic and lose control, or block it and become invisible even to legitimate agents that could find and recommend them.
AI agents face the same verification problem from the other side. Like People, they can mistake fake websites, copied badges or manipulated trust signals for the real thing. If that leads to a harmful recommendation, the disclosure of data or a fraudulent transaction, the question quickly becomes: who is liable for the damage?
Mutual verification starts with identity.
#trstd <protocol> connects verifiable Brand identity and website authenticity with agent identity, operator, intent and relevant mandates. This establishes who is interacting and what the agent is authorised to do. Identity starts the trust process, but does not determine the outcome on its own.
Brands and AI verify each other through #trstd <protocol>. Brands provide: verified identity, website authenticity, authentic experience signals, assurance & protection, risk signals, proof & provenance. AI agents provide: authentication, assurance, behavioural standing, evidence confidence, capability & context, freshness.
Observed behaviour adds evidence.
Verified interactions provide evidence of whether an agent respected policies, stayed within its mandate and produced the expected outcome. #trstd Intelligence uses that evidence to derive explainable behavioural standing for a specific capability and context. Evidence quality, corroboration and freshness matter more than volume.
Brands gain control of AI traffic.
Authentication, assurance, behavioural standing, evidence confidence, reasons, constraints and freshness remain separate policy inputs. Brands apply their own rules and retain the final decision for each request: OBSERVE, ALLOW, LIMIT, CHALLENGE or DENY. Mandatory safety conditions can override standing.
Verified interactions strengthen the evidence base.
Each verified interaction can add attributable evidence to the #trstd trust context. Independent and corroborated evidence carries more weight than volume, while incidents, contradictions and remediation remain visible. These signals can support future interactions without becoming a universal trust score or silently transferring between capabilities and contexts.
One verified interaction
Connected to who was involved and what actually happened.
Perspective A
What was requested, done or experienced.
Perspective B
What was delivered, observed or confirmed.
One verified interaction
Connected to who was involved and what actually happened.
Perspective A
What was requested, done or experienced.
Perspective B
What was delivered, observed or confirmed.
One verified interaction
Connected to who was involved and what actually happened.
Perspective A
What was requested, done or experienced.
Perspective B
What was delivered, observed or confirmed.
Designed as a trust layer for the AI era. Built on recognised standards.
#trstd. The infrastructure that makes trust verifiable.
Verified interactions Verified outcomes Verifiable reputation Capability-specific standing Evidence confidence Reasons, constraints & freshness