Agent
E-Commerce AIYour store, with a brain.
Improve product recommendations, support, inventory planning, and customer insights. We configure the workflow, connect your tools, test the edge cases and keep the agent aligned with your team after launch.
The short version
E-Commerce AI That Helps Online Stores Sell More. It connects the tools you already use, follows your rules, and keeps a human review step where it matters.
What it does
Capabilities,
in plain words
No jargon, no magic. Here's what the agent actually handles.
Recommend the right products
Personalised product suggestions tuned per-shopper, refreshed on every page view, with full-funnel attribution.
Handle support 24/7
An agent that knows your catalog, order data, and return policy answers shipping, sizing, and refund questions instantly.
Forecast demand by SKU
Predicts stockouts and overstock weeks ahead so buying and logistics teams plan instead of react.
Rescue carts intelligently
Triggers context-aware messages — not generic 'you left something' blasts — based on the reason the shopper bailed.
Detect anomalies
Catches pricing errors, dropping conversion rates, and unusual return spikes the moment they happen, not next quarter.
Power merchandising decisions
Surfaces which collections, bundles, and price points actually drive margin — beyond what the platform analytics show.
How it works
A short,
honest loop
Every step has an inspection point. Nothing happens in a black box.
- /001/
Connect
We wire into your storefront, OMS, shipping platform, and analytics so the agent has a real-time view of the store.
- /002/
Train
Models train on your catalog, customer behavior, and historical orders — recommendations and forecasts reflect your business, not a generic baseline.
- /003/
Deploy
Recommendations land on PDPs, search, email, and cart pages. The support agent goes live in your chat with guardrails on actions like refunds.
- /004/
Improve
Weekly review of lift, accuracy, and edge cases. The system retrains on a schedule so it tracks seasonality and new SKUs.
Use cases
Where it
pays off
A few of the places teams put it to work.
Apparel personalization
A fashion brand replaced 'people also bought' with intent-aware recommendations and lifted AOV without changing the catalog.
Support deflection
A DTC brand handled 60% of shipping and sizing tickets without a human, with escalation for anything refund-related.
Holiday demand planning
A home-goods seller forecasted Q4 stock at SKU level and avoided both stockouts and post-holiday markdown.
Integrations
Plays nice with
your stack
Connects with the tools you already use. Don't see yours? Ask us.
- /001/Shopify
- /002/WooCommerce
- /003/BigCommerce
- /004/Magento
- /005/Klaviyo
- /006/Gorgias
- /007/Zendesk
- /008/Stripe
- /009/ShipStation
- /010/Google Analytics
What you get
What ships
with it
You walk away with a working system, clear docs and a team that knows how to run it.
- /001/Personalization, search, and recommendation surfaces live on the storefront
- /002/A configured support agent connected to your helpdesk with guardrails
- /003/Forecasting dashboards for buying, marketing, and ops
- /004/A/B test framework to measure lift on every change
- /005/Onboarding for merchandising, support, and ops teams
FAQs
Questions teams
ask us
Short, direct answers to what comes up most in discovery. Didn't find yours? Just ask ↗
It can — but only with the guardrails your team defines. Most clients start with read-only Q&A and add actions as trust builds.
Recommendations and search refresh on every catalog sync. New SKUs cold-start using attribute similarity until they earn behavioral signal.
Six months of order data is plenty. Less than that works, but expect a few weeks of personalisation lift catching up to mature signal.
Recommendations render at edge with sub-100ms response. We benchmark Core Web Vitals before and after launch.
More agents
The rest of
the crew
Most teams start with one and add another once the first one earns its keep.
Your move
See it on your
own data
A 30-minute discovery call covers your workflow, what E-Commerce AI would touch, and an honest answer on fit.