Your customers find the bugs before you do. Tower changes that — every defect named, screenshotted, and written as a ticket before anyone bounces.
0 integration needed every run makes the system better 97% of findings actionable
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The banner as a visitor meets it. Five defects, none of them announced.
Agents take it apart, region by region. Each one measured, each one captured.
The banner rebuilt from its own findings. Nothing here was guessed.
Analytics says a page under-performs. Tower says why — with the screen to prove it.
Agents browse your store on schedule — search, filters, checkout, translations — and surface issues before they reach real users. Each finding arrives with its screenshot and byte-exact quotes from the page. What serves as proof is never generated by a model.
Tower reads your store in production the same way your customers do — public pages only, no access, no snippet, no deploy. Your first audit runs tonight, not next quarter.
Thousands of products, multiple languages, external supplier feeds. Nobody on your team re-reads 400 product pages — Tower does, every run, and only escalates what costs conversions.
Each one owns a surface, finds what costs you sales, and brings back the screen that proves it.
All seven agents +Browses like a buyer with intent: home, category, search, two product pages, the cart. Catches what only shows when you compare two products, like a description copied from a supplier.
Types the queries your customers type and compares the answers. A product found under one name and missing under another. A result count that contradicts the list.
Checks that delivery, returns, stock and payment are shown where the doubt is born. A delivery time buried in the footer is not on the product page.
Walks every step of checkout and flags the ones that demand effort without explaining why: the account wall, the surprise at the cart, the field nobody understands.
We train a model specialised in e-commerce CRO, with its own evaluation of success — built on hundreds of stores and conversion research. A finding doesn’t ship until the loop says so.
A model specialised in conversion defects, with its own evaluation of success — built on hundreds of e-commerce stores and CRO research, not general web data.
Each finding runs the evaluation loop: challenged, scored, shipped or killed. That filter is how we reach 97% actionable findings per run.
The agent learns permanently. Your verdicts feed back into training, the model narrows on what converts, and the next run outperforms the last.
Small, dated, reversible. You judge before we ever talk integration — and every verdict you give trains the watch.
No integration, no access, no contract. You get the findings with their captures — the whole run is on us, because proof beats pitch.
Actionable, false, or noise — your verdict, one keystroke each. It proves the value better than any pitch, this page included.
Tower does. First audit free — you judge every finding yourself.
