StoreHero: We Build Your AI Teammates

StoreHero now builds your AI teammates. It's a service, not another tool to learn: we work with your team to build the AI teammates that run your ecommerce business more efficiently and more profitably, then we keep them running. You don't need to know what an agent or a model is. You need to know where your time and margin go, and that's what we find out first.

Most brands already use AI, just not where the money is. Three in four ecommerce owners use AI tools, but among those who do, content generation is the top use at 69%, with marketing next at 38%, according to Shopify's merchant survey. The bigger prize sits in the unglamorous work in the middle of the business: the person reconciling 3PL invoices by hand, the product uploads that eat a week, the software that duplicates something AI can already do, the shipping and payment fees nobody has audited in a year.

The limit isn't the models or what they cost to run. It's context. Give a capable AI system enough context about how your business works, from the numbers to who does what each week, and you can rethink how the whole operation runs, not just write better emails. Building that context is the work we do with you.

What is an AI teammate?

An AI teammate is a recurring piece of work that AI does for a named person on your team, on your real numbers: a skill or agent with a schedule, an owner and an output someone acts on. It isn't a chatbot on your storefront and it isn't a dashboard. It's closer to a very fast assistant who never forgets the Monday report.

Here's the kind of work they take on:

• Finance and admin: reconciling 3PL and supplier invoices, flagging eligible duty refunds, auditing shipping costs, payment fees and COGS every month.
• Operations: uploading new products to Shopify, processing B2B and wholesale orders, checking stock against what you're spending ads on.
• Marketing: checking ad spend on Meta and Google Ads against target margin every day, reviewing creative by profit rather than ROAS, catching discount codes that lose money.
• Reporting: a Monday profit briefing across Shopify, ads and email, with one ranked task list for the week.

Why we built it as a service

Brands don't need another AI tool. They need someone to understand the whole business, find where money is being wasted and actually implement the changes. Most founders can't specify what an AI-run version of their business looks like, because they've never seen one, and they shouldn't have to. So we don't ask you to design it. We get inside the business and show you.

It also takes ecommerce know-how most AI consultants don't have. StoreHero already runs profit data for more than 1,000 ecommerce brands, so we start with the integrations, the financial model and a language of contribution margin, CAC and inventory that your team already speaks.

How it works: discovery first, then 90 days

Discovery: interviews and the P&L

Every engagement starts the same way. We sit down with each person on your team and ask how their week really goes: what they do by hand, what they copy between tools, what they'd stop doing tomorrow if they could. Then we go through your P&L line by line, along with every software subscription, agency relationship and supplier agreement.

You come out of discovery with a ranked list of where time and margin are leaking, each item costed in hours and dollars, and the first AI teammates we'd build to fix them.

Days 1–30: make the data margin-true

We connect Shopify, your ad platforms, email, subscriptions and costs (COGS per SKU, pick and pack, shipping paid, payment fees and returns) so every order carries its full cost. The test at day 30: can you say what you made on a single order after every cost, and does last month's total agree with your accountant's to within a couple of percent? If you can't answer that, no AI can either. Our profitability tracking guide walks through the cost lines.

Days 31–60: agree the definitions

AI gets numbers wrong when nobody has agreed what "margin" means. So we write down the 8 numbers you make decisions on, each with a formula, an owner and a target: net sales, contribution margin in dollars, new-customer CAC, MER, breakeven ROAS per product, target margin by channel, stock status, and what counts as a new customer. That's your semantic layer, the one set of definitions every report and every AI reads from.

Days 61–90: build the teammates

Now AI can do real work, because it's reading clean data with agreed definitions. We connect it through the StoreHero MCP, which gives Claude and ChatGPT your orders, ad spend, COGS and contribution margin with the definitions already applied. Then we build the teammates from your discovery list, schedule them and train your team to act on what they produce. These are the ones that usually pay back first, costed for an illustrative brand with team time at $50 an hour:

That's about 10 hours a week, or $500 at $50 an hour, before counting a dollar of margin found. The spend and discount teammates are usually where the bigger money is, because they catch losses a revenue dashboard hides.

After day 90: we keep them running

Every finding becomes a task with an owner, a priority and a clear do more or do less, reviewed on a fixed weekly rhythm so nothing piles up unread. We tune the teammates every month as the business changes, retire any that nobody acts on, and take on more of the work as each one proves itself in your numbers.

Will AI teammates replace my team?

That isn't the promise, and we don't make it until a teammate has proved it does the job as well or better. The teammates take the repetitive work, like the uploads, the reconciliations and the Monday spreadsheet, and prepare the decisions. Your people keep the judgment, the exceptions and the quality, and get back the hours they were spending on admin. The brands that get the most from it end up running leaner, with a smaller, sharper team that spends its week on the decisions that move profit.

Who it's for

It's built for Shopify and DTC brands doing roughly $5 million a year or more, where the team is big enough that a lot of the week goes on manual work, and small enough that every hour shows up in the P&L. It usually starts with the founder, COO or head of ecommerce, because discovery needs someone who can see the whole business.

If you'd rather do it yourself first, Claude or ChatGPT plus a spreadsheet will take you a long way, and our free AI Skills Library has ready-made versions of several teammates, including a discount code profitability check and daily inventory actions. Most brands that try it hit the same wall: nobody owns the definitions, and the outputs stop getting read. That's the part we take on.

Key takeaways

• StoreHero now builds your AI teammates: a service, not another tool, so no AI knowledge is needed on your side.
• An AI teammate is a recurring job AI does for a named person on your real numbers, with a schedule, an owner and an output someone acts on.
• Every engagement starts with discovery: interviews with each person on the team, then the P&L, software, agencies and suppliers line by line.
• Days 1–30 make the data margin-true, days 31–60 agree the definitions AI uses, and days 61–90 build and schedule the teammates.
• The first teammates (profit briefing, spend check, discount check, stock versus ads) save about 10 hours a week in an illustrative brand, before any margin found.
• Teammates take the repetitive work and prepare decisions; your people keep the judgment, and we keep the teammates tuned every month.

Frequently asked questions

Sources

• Shopify: AI in ecommerce (merchant survey figures)
• Model Context Protocol: What is MCP?
• dbt: The dbt Semantic Layer