E-commerce
AI automation for e-commerce brands
E-commerce ops is a thousand small manual checks: invoices against orders, weights against specs, prices against markets, listings against rule books. Each one is small; together they’re a full-time job that scales with your catalog. That job is automatable.
Where the money leaks
Supplier documents checked by hand
Invoices, packing lists, and casting sheets get eyeballed and re-typed. Errors slip through precisely because the work is numbing.
Catalog math doesn’t scale
One product means dozens of variants, each with its own cost, weight, and margin calculation. Spreadsheet formulas only get you so far before someone pastes over the wrong cell.
Back-office knowledge lives in heads
Returns, shipping, special processes: they work because a specific person knows the steps. That person takes vacations.
What I build for e-commerce
Document pipelines with OCR
Scanned supplier documents read by machine vision, parsed into structured records, checked against thresholds and live market data. Humans only see the exceptions. For a jewelry client: every casting invoice checked, weight discrepancies flagged at 0.03 DWT, metal rates verified against live gold/platinum spot prices.
Rule-based catalog generation
Encode your variant logic once (metals, sizes, stones, margins) and generate complete, correct Shopify listings from a single style row.
Internal ops platform
Modular mini-apps for returns, shipping, receiving: one login, per-user access, every process captured in software instead of tribal knowledge.
Proof, not promises
Built in production for a US fine-jewelry retailer with 23 years in business: invoice OCR with live spot-price verification, an internal operations platform (~25k lines of code), and a variant generator that turns one style row into dozens of correct Shopify listings.
Read the full case studyCommon questions
We’re on Shopify/Magento. Does that matter?
No. I’ve shipped against both (a Magento storefront rebuild and Shopify catalog automation). The automation layer sits on your data and APIs, whatever the platform.
Our processes are weird. Can automation handle that?
Weird processes are the strongest case for custom code: SaaS tools are built for the average process, and yours isn’t average. The 0.03-DWT weight gate above exists because that client’s business needed exactly that rule.
Find the leaks in your operation.
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