Xinan Intelligence Technology · 2026-10-05

Commerce-agent system brief

Connect product research, content, support, orders and analytics; automate routine tasks with human control of critical decisions.

Original AI-generated concept scene; not a real customer, device or project result.

Business and permissions

Map stores, platforms, products, markets, logistics and support. Use authorized official APIs; do not scrape unauthorized data or bypass platform controls. Separate catalog, ads, refunds and payment permissions.

Automation workflows

Connect research, drafts, checks, approvals, publishing and receipts. Automate low-risk tasks; bound and approve price, ad budget, refund and fund actions. Absolute unattended operation is not promised.

Deliverables

Deliver workflows, mappings, roles, review rules, retries and audits. Stores remain customer-controlled; manage data, tokens and provider fees contractually, with shutdown and human takeover.

What we can develop

Product research, selection assistance, authorized assets and multilingual drafts.
Support knowledge, order lookup, ticket routing and after-sales collaboration.
Controlled integration of inventory, fulfillment, advertising and analytics.
Approvals, spend limits, separated permissions, audit logs and human takeover.
Brand stores, multi-store operations and multilingual catalogs.
Product imagery, content review, rights checks and publishing approvals.
Support, after-sales, shipment tracking, exceptions and reporting.
Supply, inventory, ERP/WMS and auditable operational automation.

From requirements to handover

Requirements and authorization: define the problem, owners, data and interface rights.
Plan and baseline: agree scope, risks, budget, deliverables and acceptance.
Prototype and pilot: validate critical flows and recovery in controlled environments.
Integration and acceptance: review test evidence, not demonstrations alone.
Handover and maintenance: deliver docs, training, access, backups and iteration plans.

Scenario and solution studies

Concept studies illustrate design and acceptance, not completed customer projects.

Multilingual catalog-launch assistant

Project context: Product data needs drafts for multiple markets.

Solution approach: Draft from authorized facts and images, check claims and restrictions, publish after approval.

Acceptance focus: Check language, specification consistency, rights and withdrawal.

Order exceptions and support

Project context: Delays and stock conflicts need timely detection.

Solution approach: Receive authorized events, reconcile and recommend actions; humans approve refunds and address changes.

Acceptance focus: No duplicate actions from repeated events; explain false alarms and log takeover.

Catalog asset and publishing review

Project context: Multi-market catalogs need consistent facts, style and rights.

Solution approach: Organize authorized assets and rules, version drafts and publish to approved stores after review.

Acceptance focus: Test provenance, false-claim blocking, publishing rights and rollback.

Cross-border support and operations desk

Project context: Cross-time-zone support needs order states, rules and languages.

Solution approach: Build permissioned knowledge and order lookup, draft replies and escalate disputes/refunds.

Acceptance focus: Check facts, languages, isolation, handling time and approvals.

Data and acceptance measures

Measures guide project testing. Except for cited industry definitions, they are not achieved Xinan results or performance promises.

Completion: segment authorized tasks and separate escalation and refusal.
Order integrity: duplicate actions, stock differences and reconciliation failures, not task volume as revenue.
Costs: separate models, platforms, ads and fulfillment; stop or approve overspend.
Reconciliation discrepancy = inconsistent / checked records; separate stock, orders and payments.
Segment rejected content by reason; volume does not prove compliance or quality.
Separate GMV, net sales, refunds, taxes and ads; transaction volume is not profit.

Sources and industry references

Third-party material is technical reference, not a partnership or endorsement. Checked: 2026-10-05.

Shopify API idempotent requests

Implementation reference: supported APIs use keys to prevent duplicates; verify each interface.

NIST AI RMF / Generative AI Profile

Organize AI validation around risk identification, measurement and management; not a certification.

Before we start, tell us

Markets, platforms, SKU volume, official API rights, logistics, spend limits and approvers.

Delivery and usage boundaries

Autonomous means automation within approved scope, not zero oversight. No platform evasion, fake reviews, impersonation or unauthorized fund actions.