Solutions / E-commerce
From generic support tickets to personalized, resolved-on-first-contact service
The problem, plainly
Support volume scales faster than support headcount, and most ticket time is spent answering the same handful of questions: order status, return policy, sizing, compatibility. Meanwhile, product recommendations and post-purchase follow-up are often left entirely manual or skipped outright, leaving revenue on the table.
Our approach for e-commerce
We connect your product catalog, order history, and policy documentation into a support and recommendation layer that resolves the repetitive volume automatically and escalates genuinely novel issues to your team. The same underlying data powers personalized follow-up and recommendation flows, so the AI investment pays for itself on both the cost and revenue side.
Use cases
Order-aware customer support
Support that can see order status, shipping data, and policy terms directly, resolving routine tickets without a human touch and escalating clearly when it can’t.
Personalized post-purchase follow-up
Automated, context-aware follow-up sequences based on what a customer actually bought, increasing repeat purchase rate without manual segmentation work.
Catalog-grounded product recommendations
Recommendation logic grounded in your actual inventory and product data, avoiding the generic suggestions that come from off-the-shelf recommendation widgets.