A practical agent-readable product data schema for products, variants, offers, evidence and compatibility, with validation rules and failing fixtures.
Author
Intelliger Engineering
Implementation analysis on agent authority, MCP control, agentic commerce, payments and evidence, with explicit preview and production boundaries.
Editorial focus
- Agent authority and MCP control
- Agentic payments and transaction evidence
- Agentic commerce infrastructure
- OATI implementation and assurance boundaries
Corrections and source questions can be sent to hello@intelliger.ai.
Published articles
Agentic AI security needs more than authentication. AI agent authorization, mandates, revocation and signed evidence protect enterprise transactions safely.
An agentic commerce platform needs merchant connectors, live state, delegated authority, receipts, outcome data and routing to scale safely across channels.
Compare ACP, UCP, AP2, A2A and MCP, then build a canonical core with versioned adapters that survives the agentic commerce protocol race across channels.
Agentic payments architecture for separating model proposals from deterministic authorization, exact approval, payment execution and verifiable evidence.
Build an AI agent audit trail that combines operational logs with signed receipts, request binding, lifecycle evidence and independent verification.
Design AI negotiation with typed offers, deterministic price floors, exact approvals, concurrency control and live state so every discount is valid at runtime.
Learn AI search optimization for commerce with machine-readable products, verified live state, published capabilities and agent selection metrics at scale.
Compare AP2 payment mandates with broader enterprise agent authority across identity, purpose, tools, data, delegation, policy, execution and evidence.
Build AI training data for commerce from verified state, action and outcome trajectories while preserving causality limits, consent and isolation by design.
A production ecommerce product search algorithm using typed filters, hybrid retrieval, compatibility, live inventory and outcome-aware reranking at scale.
Authorize an MCP tool call by verifying identity, mandate, policy and exact request arguments before execution, with replay-safe evidence afterward.
Design live commerce state for AI shopping agents with authoritative reads, reservations, expiry, idempotent retries and checkout reconciliation.
Compare MCP gateways and API gateways by policy subject, request binding, delegated authority, revocation, replay protection and action evidence.
Make an online store visible to AI shopping agents with structured product data, live inventory, executable capabilities and measurable discovery signals.
AI agent authorization guide for binding verified identity, delegated authority, policy, approval and evidence to each consequential enterprise request.
Build ecommerce AI search that combines hybrid retrieval with authoritative price, inventory and delivery checks, then evaluate the complete path.
Design product data, retrieval, live-state checks and evaluations that help AI agents find eligible products without inventing price or availability.
Build accounts payable automation that prevents duplicate and wrong-invoice payments with stable identity, idempotency, durable state and reconciliation.
AI agent observability needs more than logs. Learn how signed action receipts bind requests, authority, policy, execution and results for verification.
Secure delegation in multi-agent systems with bounded mandates, subset checks, shared budgets, runtime binding and deterministic authorization failures.
A fail-open vs fail-closed framework for enterprise AI agents facing stale revocation data, replay-store failures and trust control-plane outages.
An AI agent architecture that turns MCP tool calls into auditable transactions using identity, mandates, request binding, approvals and signed receipts.
A safer RWA tokenization architecture that binds agent authority, reserve evidence, approvals, issuance capacity and wallet execution to each mint.
MCP authorization for enterprise agents: bind identity, delegated authority, policy, approvals, execution and signed evidence to every consequential tool call.
Use just-in-time access to run production AI agents without standing credentials, with scoped mandates, deterministic policy and short-lived capabilities.
Prevent replay attacks against AI agents by binding signatures to request context, mandates, nonce state, idempotency and deterministic verification order.
Secure enterprise AI agents when only one company adopts the trust layer, using identity mapping, bounded authority, policy and unilateral receipts.