Ecommerce
Agentic AI for ecommerce — quote-to-cash, chargeback mitigation, inventory automation and personalised customer experience running in production across EU markets.
What makes ecommerce hard for AI
Catalogue data is inconsistent at scale
Attributes arrive from many suppliers in many formats. Duplicate and near-duplicate records break both merchandising and reporting, and they compound quietly.
Margin is decided per order
Discounting, shipping and returns interact. Optimising conversion without modelling margin reliably produces more revenue and less profit.
Disputes are evidence exercises
Chargeback outcomes depend on assembling order, delivery and communication records within tight deadlines. Most losses are administrative rather than fraudulent.
Where the value concentrates
- Quote-to-cash. Profit-aware pricing and approval that protects margin at deal speed.
- Chargeback mitigation. Automated evidence assembly against deadlines.
- Catalogue quality. Cross-platform deduplication and attribute enrichment.
- Inventory and replenishment. Forecast-driven ordering against supply constraints.
What the economics look like
Chargeback win rate and catalogue quality both produce fast, attributable numbers, which makes them good first projects. Personalisation matters more in the long run but is harder to measure cleanly in a first quarter.
How we build it
We connect storefront, ERP, payment and logistics systems so agents can act on complete order context rather than a fragment of it.
Related work
Starting smaller
Smaller merchants usually start with chargeback evidence assembly — narrow, deadline-driven, and with an unambiguous success measure.
Questions we get from merchants
What gives the fastest measurable return?
Chargeback evidence assembly. Deadlines are fixed, the evidence is scattered across systems, and win rate is measured directly — so the before-and-after number is unambiguous within a quarter.
How do we stop personalisation from eroding margin?
Model margin per order alongside conversion, including shipping and expected returns. Optimising conversion alone reliably increases revenue and reduces profit, and reporting built around top-line growth will not reveal it.
Our catalogue has thousands of duplicates. Can agents fix that?
Yes, and it is a well-suited task — resolving near-duplicates across CRM, ERP and storefront while preserving downstream references. The constraint is not detection but doing the merge without breaking existing links.
Do we need to replace our platform?
No. Agents integrate with the storefront, ERP and payment systems you already run. Platform replacement is a separate decision and should not be bundled into an AI programme.