Mirakl’s AI agents, paired with ChatGPT Enterprise and Mirakl Nexus, accelerate commerce operations. Teams create documentation faster, handle customer support more intelligently, and prepare for agent‑native journeys where trusted agents discover, transact and manage post‑purchase—improving speed, accuracy and customer experience across marketplaces and retail media.

What’s New & Why It Matters

Agent‑native (agentic) commerce: An architecture where AI agents act on behalf of shoppers, sellers and operators—discovering products, negotiating constraints, transacting, and managing post‑purchase steps. It reduces manual effort and makes experiences more responsive and contextual.

Mirakl Nexus: A neutral, AI‑native backbone designed for agent‑led commerce. It provides real‑time product and inventory access across thousands of sellers, native orchestration for checkout/payments/refunds/tax, trust & compliance enforcement, and a unified data model—so agents can operate safely at enterprise scale.

ChatGPT Enterprise inside Mirakl workflows: Enterprise‑grade controls and speed help teams accelerate internal documentation, knowledge retrieval and multilingual support, with strong governance.

Practical Rollout (Step‑by‑Step)

1. Identify high‑impact use cases (4–6 weeks)
   Prioritise: internal technical documentation, support macro drafting, catalog onboarding, and seller enablement. Define KPIs such as time‑to‑first‑response, documentation cycle time, deflection rate, and onboarding throughput.

2. Stand up an agentic foundation

   • Data layer: map catalog, policy and SLA data to a unified model; patch weak taxonomy areas.

   • Mirakl Nexus: enable real‑time APIs for product, price and stock; connect payments, taxes, refunds and compliance to agent workflows.

   • Security & governance: enterprise‑grade access control; human‑in‑the‑loop for high‑risk actions; audit logs.

3. Accelerate documentation with ChatGPT Enterprise

   • Create approved prompts + Retrieval (connect knowledge bases).

   • Standardise outputs (templates for runbooks, release notes, support KBs).

   • Track: cycle time per doc, review rounds, reuse rate.

4. Smarter customer support

   • Use agents for triage, intent detection, summary and suggested replies; route to humans for exceptions.

   • Close the loop with automatic post‑contact summaries and ticket tagging to improve analytics.

5. Agent‑native commerce pilots

   • Start with constrained journeys: price/stock checks, basket building under rules, returns/claims management.

   • Enable multi‑language support and 24/7 coverage.

   • Stage‑gate rollout by risk class (read‑only → limited write → full orchestration with approvals).

6. Measurement & value story

   • Operational: % faster doc creation; first‑contact resolution; support efficiency; onboarding speed.

   • Commercial: conversion lift from cleaner catalog data; reduced time‑to‑list for sellers; ad yield if using retail media.

   • Trust: policy adherence, refund accuracy, SLA breach rate.

Example Use Cases

• Docs factory: engineer creates a draft design doc from tickets and commits; reviewer edits; system publishes to the KB with tags.

• Support assist: agent drafts multi‑language responses, cites policy and SLA, and updates the CRM with a clean summary.

• Catalog accelerator: ingest seller feeds; fix titles/attributes; reduce categorisation errors; speed up onboarding.

• Retail media operations: optimise campaigns with cleaner catalog data and agent‑ready signals.

Risks & Mitigations

• Hallucinations / policy mismatches: use retrieval + validation; require human approval for financial actions.

• Data leakage: segment environments; restrict prompts; disable training on customer data by default.

• Drift: pin models/versions; quarterly evaluation with gold‑set tasks; incident playbooks for rollbacks.

FAQs

What is agent‑native (agentic) commerce?
A model where AI agents act on behalf of users and operators to discover, transact and manage post‑purchase, under enterprise controls.

How does Mirakl Nexus help?
It provides real‑time access to product and inventory, plus native orchestration for checkout, payments, refunds and taxes—along with trust/compliance and a unified data model—so agents can operate safely at scale.

Where do AI agents deliver ROI first?
Documentation, customer support and catalog onboarding typically show the quickest wins; retail media follows as data quality improves.

Is this only for marketplaces?
No. The same capabilities apply to broader commerce—marketplaces, first‑party eCommerce, B2B distribution and retail media.