A specialty retail team had inherited an online store after the person who managed it left. We asked Omni's AI agent to take on the project: understand the setup, turn the team's priorities into clear tasks, prepare the changes, and keep a usable record as the work moved forward.
The result was a working handover. The team could inspect what the agent had changed, review preview work before release, and continue from the same project record instead of starting over. Some scoped updates reached the live store. A later product-page adjustment remained in preview while the team reviewed it.
How the agent found the opportunity
Omni’s involvement began before anyone knew the store needed help.
Through Signal Hunter, a workflow that reviews public business information, Omni identified a traditional tea business already investing in AI. That suggested a potential need for technical support, but it did not reveal the problem with its U.S. online store.
The agent researched the company, checked existing opportunity and outreach records, and sent introductory emails. A follow-up to the U.S. business brought the actual need into view: the person managing its website had left, nobody had taken over, and the team was looking for a long-term website-management partner.
Omni recorded the opportunity and prepared an initial technical assessment. The store was running on Shopify and could be improved without rebuilding it. The assessment identified an aging customized theme, overlapping apps, and interface details that needed attention.
A human team member then led the proposal and commercial discussions. The engagement progressed through payment, access, and delivery, with Omni supporting the storefront work described below.
This is an anonymized account of delivered client work. The original case article is published on Omni Care.
The store worked, but changing it was risky
An inherited storefront can look healthy because customers can still browse and buy. The risk appears when the next update arrives. The team needs to know which theme settings matter, why an app was installed, whether a mobile layout is deliberate, and what another edit might break.
For this project, the work included a seasonal announcement, mobile presentation, product-page controls, footer updates, app cleanup, and a handover record. The challenge was to move those tasks forward without losing the context behind them.
How the agent moved the project forward
The project team set priorities, reviewed changes, and authorized release. Omni carried the work through context, planning, execution, and verification while retaining the shared project record.
Omni was used as the working agent for the project, not as a one-off writing assistant.
- Reconstruct the setup. The agent gathered the inherited requirements, current theme and app state, previous decisions, and visible issues into one execution plan.
- Turn requests into bounded changes. Instead of treating “fix the store” as one vague instruction, Omni separated the work into specific tasks with an expected result and a way to check it.
- Use preview and release paths deliberately. Changes that needed visual review stayed in an unpublished preview. A change reached the live store only when the team explicitly authorized that route.
- Check the result and retain the record. The agent read the changed configuration back, inspected the rendered page where possible, and kept the request, output, review notes, and verification result together for the next task.
A concrete request, output, and review
One task was to correct the closing date on a seasonal campaign banner without disturbing the rest of the offer or its shopping link. Before changing anything, Omni checked the live value and found that it differed from the date described in the request. That check prevented the agent from editing the wrong text.
Omni then changed only the date field in the live theme. For review, it read the theme configuration back and loaded the storefront. The new date appeared once, the old date no longer appeared, and the surrounding offer, link, and other site changes were still present. The request, exact change, and checks were recorded together.
What the team gave Omni: correct one seasonal-banner date and leave the rest of the banner unchanged.
What Omni produced: one scoped theme update on the live store.
How it was reviewed: configuration readback plus a rendered-store check confirmed the new value and the unchanged surrounding content.
A later product-page task had a different status. Omni adjusted the size selector in an unpublished preview, and the team was still reviewing that version while requesting related quantity and sold-out refinements. We do not describe those adjustments as live.
What the delivered result means
The delivered work is the maintained path from request to inspected change. The inherited setup was mapped, tasks were separated, live and preview states were recorded, and the next update could continue from the same history.
Here, “verified” means the requested change was checked against the stored requirement and the resulting configuration or rendered page. It does not mean that every proposed change reached the live store, and it is not a claim about traffic, sales, conversion, or time saved.
One thing to take away
If your team inherited an online store, give an AI agent one bounded project with the real context, a clear release path, and checks that can be read back. The useful result is more than advice. It is a traceable path from a business request to an inspected outcome.
What kind of project would you want to see Omni solve next? Tell us in the comments.
Top comments (0)