Agentic AI for retail and e-commerce
Commerce runs on millions of tiny decisions — where to source an order, whether a refund is legitimate, which SKU description is wrong, why a customer is asking where their package is. Most are still made by people clicking between an OMS, a processor dashboard, and a helpdesk. We deploy agents that do that work and hold through peak.
- High-volume order & fulfillment ops
- Returns & chargeback fraud defense
- Catalog & merchandising at scale
- Omnichannel customer support
The margin lives in the back office, not the storefront
A clean checkout is a few seconds of code. Everything after it — sourcing, returns, disputes, catalog hygiene, support — is where retailers quietly bleed time and money.
A single order can fan out into a dozen downstream decisions: which warehouse or store ships it, whether to split the shipment, how to handle a partial out-of-stock, when to trigger a backorder, and what to tell the customer at each step. At Black Friday volumes those decisions arrive faster than a fulfillment team can make them, so service levels slip exactly when customer patience is thinnest.
Returns and disputes are worse. Online return rates run far above brick-and-mortar, and a meaningful slice is abuse — wardrobing, empty-box returns, and friendly fraud where a customer charges back a delivered order. Every chargeback costs you well beyond the transaction once you count fees, lost goods, and the staff time to fight it, and the representment window is short and evidence-heavy.
Then there's the catalog: thousands of SKUs with inconsistent titles, missing attributes, wrong sizes, and stale pricing — each error a conversion killer or a costly mispriced sale. This is exactly the shape of work agents do well: high-volume, rule-bound, document- and data-heavy, and bottlenecked on retrieval and reconciliation rather than on a judgment call. We automate the legwork and keep the money-moving decisions gated.
Where agents earn their keep
Concrete, bounded jobs across the order-to-resolution lifecycle — each one observable, reversible, and gated where it touches money.
Order orchestration & exceptions
Source each order to the right node, handle splits and partial stockouts, trigger backorders, and chase the exceptions — address failures, payment holds, stuck shipments — instead of leaving them in a queue.
Returns & chargeback defense
Score returns for abuse patterns, assemble representment evidence packets against the dispute reason code, and file within the network deadline — routing high-value or borderline cases to a human.
Catalog & merchandising hygiene
Normalize titles and attributes, fill missing fields, flag mispriced or duplicate SKUs, and draft on-brand product copy against your PIM — surfacing edits for sign-off, not silently overwriting.
Omnichannel customer support
Resolve WISMO, returns, and order-change requests against systems of record across chat, email, and social, with consistent answers and a clean escalation path to a live agent.
Fraud triage at authorization
Read the auth result, AVS/CVV outcome, velocity signals, and account history to recommend approve, review, or hold — never touching the PAN, always logging the rationale.
Supplier & inventory reconciliation
Match POs to ASNs and invoices, reconcile inventory counts across channels, and flag discrepancies before they become oversells or stranded stock.
A disputed return, end to end
The agent compresses the gather-and-check work; a human keeps the calls that move money or a customer relationship.
Detect
A return request or chargeback lands; the agent matches it to the order, delivery proof, prior return history, and the dispute reason code.
Score
Abuse signals are weighed — serial returns, mismatched scan weight, friendly-fraud patterns — and a clean refund is separated from a suspect one.
Assemble
For disputes, the agent builds a representment packet — proof of delivery, AVS match, terms accepted — formatted to the card network's evidence rules.
Decide
Clean low-value refunds auto-approve inside policy limits; high-value or suspect cases route to a human with the full packet. Every step is logged.
Acting on the order without touching the card
The fastest way to fail a PCI assessment is to let a new system into the cardholder data environment. We design the opposite: agents operate on tokenized references, order metadata, and processor outcomes — never the raw card number. The PAN stays inside your processor and your CDE, and the agent stays out of PCI scope.
That principle extends to the rest of your sensitive data. Customer PII, order history, and pricing models run in your environment — VPC, on-prem, or a hybrid you control — with every tool call logged and every money-moving action gated. Compliance and security are part of the architecture, not a banner you bolt on after the demo.
- Tokenized references only — never the raw PAN
- Agent stays outside PCI-DSS scope
- Customer PII kept inside your perimeter
- Approval gates on refunds, blocks, and representments
Another dashboard vs. an action-taking agent
Why a queue full of alerts is not the same as work getting done.
| A dashboard / rules engine | An Automatic.co agent | |
|---|---|---|
| Order exceptions | Surfaced in a queue for someone | Worked and resolved, gated where needed |
| Chargebacks | Alert; you file it manually | Evidence packet assembled and filed on time |
| Catalog errors | Flagged in a report | Fixed or drafted for one-click sign-off |
| Peak load | Same team, more overtime | Scales horizontally, 24/7, supervised |
| Card data | Often pulled into scope | Tokenized only — stays out of PCI scope |
Frequently asked questions
Will agents touch cardholder data, and how do you stay PCI-compliant?
No. Agents work against tokenized references and order metadata, never the raw PAN. Card data stays inside your payment processor and PCI-DSS cardholder data environment; the agent reads the token, the authorization result, and the AVS/CVV outcome to make a routing or refund recommendation. That keeps the agent out of PCI scope and keeps your attestation intact, while still letting it act on the parts of the order that matter.
Can an agent issue a refund or block a customer on its own?
Within bounded limits, yes — above them, no. You set thresholds: refunds under a configurable dollar amount on a clean account auto-approve, while high-value refunds, chargeback representments, and account blocks route to a human with the evidence packet attached. The agent does the assembly and the recommendation; a person owns anything that touches money at scale or a customer relationship.
How do agents hold up during Black Friday and other peak spikes?
Agents scale horizontally and don't get tired at 3 a.m. on Cyber Monday, which is exactly when WISMO tickets and fraud attempts both peak. We load-test against your historical peak multiples, set rate limits and graceful degradation on every downstream system, and keep humans in the loop on the edge cases so a 10x volume day doesn't become a 10x error day.
Do agents replace our OMS, PIM, or helpdesk?
No — they act on top of them. Agents read and write through your existing Shopify, NetSuite, Salesforce Commerce, Zendesk, or a custom OMS via APIs and webhooks, so the system of record stays the system of record. Every order update, catalog edit, and ticket resolution is logged and reversible.
Bring your worst peak-season bottleneck.
One working session to map a single high-volume retail workflow — returns, order ops, catalog, or support — and the gated, audited agent that can run it.