Zegates
All solutions
AI FOR RETAIL

Triggered campaigns and stock intelligence for retailers who already own the data.

Small and medium retailers already produce a record of every transaction. The AI just reads it and acts on it — matched customer campaigns, honest reorder decisions, cross-sell prompts at the counter.

Use cases

What we build here

Each is a real workflow, shipped or ready to ship. Pick the one that hurts the most first.

CAMPAIGN

Stock announcements triggered by intake

New consignment arrives. The system messages only the customers who bought that category, in that size, in that price band. Six messages beat forty.

MERCH

Reorder decisions from real sell-through

Which sizes actually sell, which ones end up discounted. Buying decisions grounded in evidence, not gut feel or last season's habit.

RETENTION

Customer retention flags

Regulars whose purchase pattern has broken surface as a soft reach-out list before they are gone for good.

BASKET

Basket analysis and cross-sell prompts

Which products actually sell together informs both the shelf and the counter suggestion. The prompt reads to the customer as helpful, not pushy.

ANOMALY

Anomaly detection on POS activity

Voids, refunds, and discounts profiled against normal store behaviour. Till-level irregularities surface without manual review.

How we build it

Small releases into a real production system.

  1. Read the POS data you already have

    Most small retailers capture rich transaction data and never look at it. The first job is turning that record into a decision surface.

  2. Ship one workflow that moves margin

    Triggered campaigns, buying assistance, or till anomaly detection. Start with the one whose ROI is easiest to measure.

  3. Extend across store and online

    One inventory position, one customer record. The same intelligence works whether the sale happens in the shop or the web store.

Plugs into

Your existing tools stay yours.

We read and write through the systems your team already uses. No parallel database of truth, no rip-and-replace.

NetliseShopifyLightspeedSquareKlaviyoWhatsApp BusinessStripeOpenAI
The gap between large and small retailers was never a gap in intelligence. It was a gap in instrumentation.

Let's discuss your idea with us