Catalogues that clean themselves, demand you can actually plan around, search that understands what a shopper means, and support that knows the order it's talking about. Built into the stack you already run — Shopify or your storefront, your ERP, marketplaces and 3PL — and engineered to stay accurate through peak, with a person on the calls that carry real money.
A model that's confidently wrong about stock, price or a customer's order doesn't save time — it manufactures refunds, angry tickets and a manual clean-up on your busiest day.
So we build the opposite. Forecasts and answers are grounded in your own data — the live catalogue, the actual order, the current stock position — and wired into the systems you already run: your storefront, ERP, PIM, marketplaces and 3PL. No parallel spreadsheet to maintain, and every output traceable back to the record it came from.
Where a decision moves money — a price change, a markdown, a bulk reorder, a refund — a person stays in control and the AI does the reading, drafting and sorting underneath them. And because retail traffic isn't flat, we engineer for the peak, not the average, and monitor it so it still works the week after launch, not just on demo day.
Real AI solutions for your operation, built into the tools you already run.
Supplier feeds, spec sheets and product images read and turned into clean, structured catalogue data — attributes, variants and categories mapped to your own taxonomy. It drafts titles, descriptions and metadata in your brand voice, dedupes near-identical SKUs, and flags the gaps a merchandiser should fill. Every attribute stays traceable back to the source it came from.
SKU- and location-level demand forecasts that account for seasonality, promotions and the launch you have coming, turned into reorder points, size curves and allocation suggestions. It surfaces the lines about to stock out and the stock about to age, and proposes the markdown before it's too late. A buyer reviews and decides — the model does the arithmetic, not the gambling.
Search that understands "waterproof jacket under £100" rather than matching keywords, with typo and synonym handling built in. Recommendations and category ordering personalised to what a shopper is actually doing, wired into your storefront and analytics. You keep the merchandising rules; the model does the ranking underneath them.
Assistants grounded in the customer's own orders, shipping status, returns and your policy docs — so "where's my order?", a return or a sizing question gets a real answer, not a guess. When something is out of scope or high-stakes, it hands off to an agent with the full context attached. Each conversation is scoped to one customer's data, and every answer is inspectable.
Free-text return reasons and product reviews read into structured themes, so a defect or sizing problem shows up as a pattern instead of a hunch. Marketplace and 3PL payouts reconciled against your orders to catch the fees, short-payments and chargebacks that quietly erode margin. Exceptions are surfaced for a person to action, with the underlying records linked.
Start with a short assessment. We map where AI pays off first in your operation, before you commit. See the assessment →
We don't only describe this. We run it.
Reef runs a production system for an accounting firm that reads documents from email and WhatsApp and assembles a structured monthly report per client, across dozens of clients. See how it works →
The engineering that keeps AI accurate and running under load — source-linked outputs, a person on the calls that move money, and monitoring for real traffic — is exactly what retail needs when the season spikes.
Into your environment, not ours to keep. We build inside your cloud or a tenant you control, minimise the personal data a workflow touches, and don't hand your catalogue or customers to a third party to train on. Access is scoped, so an assistant only ever sees the one customer or order it's answering about.
Yes — integration is the point, not an afterthought. We connect through the APIs, PIM, WMS and marketplace feeds you already have, so the AI reads and writes to your live systems rather than living in a separate tool. No rip-and-replace, and no asking your team to key data twice.
No. It takes the repetitive load — enriching listings, chasing stock signals, answering "where's my order?" — off their plate so they spend time on buying decisions, brand and the customers who need a human. The judgement calls stay with your people; the model just clears the queue in front of them.
One high-volume workflow you can measure — catalogue enrichment, WISMO tickets, or forecasting for a category that keeps stocking out. We ship that into production, prove it holds up under real traffic, then widen from a system that's already earning, rather than a big-bang rollout that stalls.
Reef TRH