Seel started off as post-purchase infrastructure. We help merchants reimagine the customer journey after checkout, helping them transform returns and refunds from a risk center to a loyalty builder. 

It was a clear problem to solve. But the lines became blurry as we started serving merchants across different product types, markets, and shopper volumes. 

It soon became clear that we were sitting at the operational core of e-commerce.

We weren't just helping shoppers get refunds faster. We were helping operations leaders rearchitect how they worked. 

Merchants were partnering with us to restructure how support tickets moved through their team, free up warehouse capacity, and redeploy headcount to revenue-generating work. Global brands would redesign their customer experience with us so shopper satisfaction would finally stop conflicting with margins needed to run the business. 

These weren't post-purchase problems. They were operations problems that began at post-purchase touchpoints. 

We built an internal AI layer

As we scaled to serve millions of shoppers a month, we hit a ceiling. Scaling headcount and third-party vendors alongside that growth wasn't a viable model. So we built an AI layer internally to work alongside our team.

It worked. Our agents were soon accelerating 80% of our ticket volume, processing millions of orders a month, and resolving routine requests at a higher rate than anything we'd run before.

But as we solved our own problem, we realized shoppers were asking us about everything else that happens after a purchase, not just their return.

Where's my order? Can I change my address? What do I do with this product issue?

Those questions pointed to something bigger. Shoppers don't experience commerce as a funnel. They experience it as one continuous thing. But the operational reality behind that experience was deeply fragmented. Returns in one tool. Support in another. Shipping protection with a separate vendor. Claims resolution cobbled together with an outsourced agency.

The shopper felt all of it as one experience. Merchants were managing five vendors to deliver it.

We heard from merchants scaling headcount 3x for peak season and spending months contracting back down. Support queues growing faster than hiring could keep up. Returned inventory eating margin with nowhere to go.

So we asked a few of them a simple question: do you want to try using what we built?

Seel Agencies for merchant operators

Seel Agencies were born out of an operational problem we solved for ourselves, and it was then recognized in the merchants we were already serving. But solving that problem forced us to rethink how we use AI entirely.

We started where most companies start: AI that responds to questions. Then we started building AI agents to take action, helping our team manage  processing returns, routing tickets without human intervention. 

Then we needed something more: multiple systems coordinating together to own an outcome end to end, the way a team of specialists would. Not an AI agent executing a task, but an AI agency running a function in a controlled and coordinated way. 

This progression from prompts to agents to agencies, mirrors where AI is heading broadly too. It also maps directly to how e-commerce operations work. 

The functions merchants have always had to staff up or outsource for aren't tasks. They're ongoing, complex, and shouldn’t have to require hours, days, or even weeks of prompt engineering and model fine-tuning to get it running properly. This is exactly when operating an AI agency would outperform running individual AI agents. 

Our AI agencies are AI-native services that execute the business functions merchants currently outsource. 

We're kicking things off with two agencies: 

The first handles customer support end to end: triaging tickets, resolving post-purchase issues, and escalating only when human judgment is required. 

The second manages returned inventory from the moment it leaves a shopper's hands through inspection, resale, and liquidation. 

What’s next? 

We have more agencies planned for the rest of the year, built on the same infrastructure and shopper data Seel developed running its own operations across 5,000+ merchants and tens of millions of shoppers monthly.

Every e-commerce operator is being asked the same question by their leadership right now: what's our AI strategy? Most are evaluating point solutions, stitching tools together, and figuring out what to build versus buy.

We're offering a different answer. Technology that arrives already trained on shopper behavior with infrastructure built for the operational complexity of real merchants, real shoppers, and real edge cases at scale.

The merchants already using Seel Agencies are reassigning headcount, cutting vendor costs, and handling more volume with a more efficient AI system design. If you want to see how that works in practice, let's talk.