aideploy --industry=retail-ecommerce --market=SG
Retail & e-commerce AI agents that survive 11.11 traffic
Singapore retail runs on spiky demand: enquiry queues that spike through the 9.9–12.12 campaign cycle, orders scattered across Shopify, Shopee, Lazada and TikTok Shop, and settlement files that never quite match the ledger. We deploy production agents against exactly that mess — 14 documented builds on our engineering hub, every one load-tested and scored on an Agent GPA evaluation before go-live.
Malaysia DigitalCertified by MDEC
HRD Corp ApprovedTraining ProviderAnchor Sprint Pte. Ltd. · UEN 202632732ZEnterprise agents delivered across SingaporeEvery agent graded before go-livePDPC · MAS TRM · IMDA
Product enquiry agent — web + WhatsApp
Answers stock, sizing, delivery and promo questions from your live catalogue, on web chat and WhatsApp Business, in the same conversation thread. After-hours enquiries convert instead of expiring in an unread inbox.
Support triage at retail volume
Reads every inbound ticket — where-is-my-order, refunds, damaged items — pulls the actual order state from your systems, and resolves or drafts the routine majority. Campaign-day spikes stop burying your support team.
Order-to-cash for omnichannel
Normalises orders from storefront and marketplaces into your ERP, then matches Shopee and Lazada settlement payouts — net of commissions and fees — against open invoices. Finance closes the month without spreadsheet archaeology.
workflows: mapped
The operational reality of Singapore retail
A Singapore retail operation is never one system. The storefront runs on Shopify or Shopline, marketplaces on Shopee, Lazada and TikTok Shop, POS in the physical outlets, WhatsApp carrying a large share of the customer conversations, and an ERP — NetSuite, SAP Business One or Odoo — holding inventory and finance together. Every campaign cycle from 9.9 to 12.12 multiplies enquiries, order exceptions and settlement files at once. The documents are concrete: order confirmations, Ninja Van and J&T waybills, return authorisations, and marketplace payout statements that arrive net of commission and never match the invoice ledger line for line. That is the workload we build agents against.
agents: in-production
The agents that fit this workload
We don't sell a chatbot bolted onto a website. Each agent is wired into the systems that hold the truth — catalogue, order management, ERP, helpdesk — with human-in-the-loop controls wherever money or a customer promise moves. Four patterns cover most of retail's pain, and all four have documented builds on our engineering hub:
- Product enquiry across web and WhatsApp, reading live stock and pricing rather than a stale FAQ
- Support triage that checks the order and shipment state in Shopify or your OMS before drafting a reply
- Order processing that validates and posts storefront and marketplace orders into NetSuite, SAP B1 or Odoo
- Cash application that matches marketplace settlement reports — commissions, vouchers, shipping rebates deducted — to open invoices in Xero or your ERP
pdpa: by-design
Customer data, handled the PDPA way
Retail agents touch names, addresses, order histories and payment references — personal data under Singapore's PDPA, administered by the PDPC. We design deployments against those expectations from day one: purpose limitation on what each agent may read, data minimisation in prompts, redaction of PII before logging, agreed retention windows, and a hard rule that your customer data is never used to train models. Outbound campaigns get Do Not Call Registry checks before an agent sends anything. To be precise: no regulator certifies or approves a vendor, and we won't pretend otherwise — what you get is an architecture built to stand up to a PDPC-grade question, in writing.
evals: agent-gpa
Evaluated before go-live, load-tested for campaign day
Every build passes an Agent GPA evaluation before it touches a customer: accuracy on your real historical tickets and orders, refusal behaviour on out-of-scope requests, escalation correctness, latency under load. Then we test the part most vendors skip — traffic. Our record is 50+ load-test audits and 30+ resilience assessments, so we rehearse your 11.11 multiple, not your Tuesday-afternoon baseline, and drill the failure modes: marketplace API throttling, webhook backlogs, WhatsApp session limits. Our lead engineers have handled 300+ production incidents; that discipline ships with the agent as SLOs, monitoring and an escalation path, not a best-effort promise.
start: scoped-pilot
Where to start
Pick the queue that hurts most — usually WISMO tickets or one marketplace's settlement files — and we scope a pilot: a bounded slice, run against your real historical data, two to six weeks, ending with a scored Agent GPA report and a fixed production quote. Low five figures SGD, and if the pilot doesn't clear the bar we agreed, you'll know exactly why, in writing. Back-plan from your campaign calendar: a pilot started now is production-hardened before the next peak, and we don't ship new automation into the week of a mega-sale.
proof · from our engineering hub
Frequently asked questions
What does a retail AI agent cost in Singapore?
Pilots land in the low five figures SGD and run two to six weeks. Production deployments — full integration, load testing, SLOs, human-in-the-loop controls — range from mid five figures into six figures SGD depending on systems and volume, fixed once scope is signed. The AgentOps retainer for monitoring and re-evaluation is a low-to-mid four-figure monthly fee. Model usage itself is usually the cheapest line: tens to a few hundred SGD per workflow per month, passed through at cost. You can estimate your own workload with the free Claude cost calculator on our engineering hub.
Can you integrate with Shopify, Shopee, Lazada and our ERP?
Yes — that integration is most of the engineering. Shopify, Shopline, Shopee, Lazada and TikTok Shop all expose APIs we build against daily; NetSuite, SAP Business One, Odoo and Xero are standard targets on the finance side, and WhatsApp Business API plus Zendesk or Freshdesk on the customer side. Where a system only exports files — a POS report, a marketplace payout statement — the agent works from the export. Nothing gets ripped out or replaced.
How do you handle customer data under the PDPA?
By design, not by disclaimer. Each agent gets purpose-limited access to the minimum data it needs, PII is redacted before logging, retention windows are agreed and enforced, and your customer data is never used for model training. Outbound messaging is checked against the Do Not Call Registry. The PDPA is administered by the PDPC and no regulator approves vendors — so we document the architecture and controls against PDPC expectations and hand you that evidence.
How long before we're live — can we make it before peak season?
A pilot runs two to six weeks; production hardening typically takes six to twelve weeks from a signed scope, including load testing at your projected campaign multiples. So the honest answer depends on your calendar: start a quarter before 11.11 and you launch battle-tested. Start the month before and we'll tell you to pilot now and go live after the peak — deploying untested automation into a mega-sale is how retailers end up on the news.
Which AI model do your agents run on, and what's your relationship with Anthropic?
We deploy Claude first where it fits and stay model-agnostic where it doesn't — retail workloads like enquiry handling and settlement matching each get the model that scores best in evaluation, at the lowest cost that clears the accuracy bar. Anchor Sprint is a member of the Anthropic Claude Partner Network. Claude and Anthropic are trademarks of Anthropic, PBC. Either way, the model choice is justified in your Agent GPA report, not asserted.
Scope a retail agent before the next campaign peak
AI Deploy is a brand of Anchor Sprint Pte. Ltd. (UEN 202632732Z), Singapore. Tell us the queue that hurts — enquiry backlog, WISMO tickets, marketplace settlements — and an engineer will come back with a scoped plan and a fixed SGD quote, or a straight answer that an agent isn't the right fix. WhatsApp +65 8749 0243.