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Case study

FreshTrends: the business we built the platform on.

An e-commerce jewelry brand on Shopify, run through one universe of modules and agents. The platform was shaped by the daily needs of a real operating business.

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The starting point

A real business with real complexity.

FreshTrends sells online, advertises on Google and Meta, runs email, ships orders and answers customers. It is the kind of established, multi-system business the platform is built for.

  • Years of accumulated systems: Shopify, ads, email, analytics, finance, support
  • Deep know-how that lived in one operator's head and scattered documents
  • Every new tool or AI assistant needed wiring to every platform again
  • No single place that said what changed, what is broken and what needs a decision

The universe

One map of the whole business.

Headquarters at the centre, departments around it, each module a planet and each agent a moon. A status dot tells you what is running, what is being set up, and what needs you.

The FreshTrends universe in the ERA ONE platform, on the Rain background
The FreshTrends universe in the platform: the organisation, its departments and modules, and the agents under them, each with a status dot. Theo, the chief of staff, sits below.
The Modules page listing Branding, Shopify ops, Finance and Security with their connected systems
Modules: each a workspace for one part of the business, with its own connected systems and an assistant that knows its job.

What is running

Modules and agents working on the real store.

  • Branding

    The real brand guide, fonts, colours and logos live in one profile. Copy, banners and video follow it.

  • Shopify ops

    The assistant reads live store data. A real catalogue change was asked for in chat and applied from its card on the live store.

  • Google Ads

    Connected to the live account. The chief of staff answers questions from it, and budget changes route to approval.

  • Security

    A Cloudflare agent finds bot and scraper floods in real traffic and proposes blocks with the evidence.

  • Site Doctor

    Daily deterministic checks and a five-minute ping on the live store, raising only what is wrong.

A day in the loop

Agents propose. A person decides.

  1. 01

    Morning

    A briefing says what changed overnight and what needs a decision.

  2. 02

    Agents work

    Scheduled agents read live data from the connected systems and write up what they found.

  3. 03

    The chief of staff reviews

    Every agent result is checked, rolled up, and anything that matters is surfaced.

  4. 04

    You approve

    Proposed changes wait in one queue. Approve, reject, or give a correction the agent learns from.

  5. 05

    The change is applied and recorded

    The platform makes the change with the vault's credentials and writes it to the audit log.

What it proves

The same platform, for your business.

Everything above is the product, not a bespoke build. The modules, skills, agents and workflows are what you load in when you sign up, and FreshTrends is the proof that they hold up on a live store.

  • Agents that touch a live store, without ever holding its keys
  • Brand and method written once, followed everywhere
  • One approval queue instead of ten dashboards
  • A system that improves as you correct it

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