AI-powered eCommerce growth

A custom storefront with native payments, an AI-powered UGC content farm, an AI SEO engine and an agentic admin — running growth, content and operations as one autonomous workflow.

Before. The brand sold through a generic SaaS storefront on stock templates, bought content production manually at agency pricing, and had founders bottlenecked on admin and operations rather than growth.

What we built. The entire stack, custom: a bespoke React commerce experience with native payment integration, an AI UGC farm producing on-brand creative, an AI SEO engine that drafts and monitors continuously, and an agentic admin running operations autonomously.

Outcome. 10× content output on-brand, with the founders describing a team three times their size — the content farm, SEO engine and agentic admin do the work, and humans make the decisions that need a human. Related: the AI UGC engine, AI for eCommerce, and custom platforms.

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Frequently Asked Questions

What are AI agents?

AI agents are software systems that perceive data, make decisions, and take multi-step actions toward a goal without needing a human to prompt each step. This differs from a simple chatbot, which only replies within a single conversation turn. In Genium's eCommerce build, the agentic admin and AI SEO engine both run continuously — drafting, monitoring, and executing operational tasks — rather than waiting to be asked.

Chatbot or agent — what's the difference?

A chatbot answers questions inside a conversation; an AI agent carries out ongoing, multi-step work and acts on its own once given a goal. The distinction matters for scoping a build: a support chatbot handles single queries, while an agent — like the AI SEO engine in Genium's eCommerce case study, which drafts and monitors content continuously — runs an entire function with minimal human intervention.

What can AI agents do for a business? What are the use cases?

AI agents can run whole operational functions — content production, SEO monitoring, back-office admin, customer messaging — as continuous autonomous workflows rather than one-off tasks. In one Genium case study, an AI UGC content farm, an AI SEO engine, and an agentic admin combined to produce 10x on-brand content output, with the founders describing the effect as adding a team three times their actual headcount, while humans stayed in charge of decisions that needed judgment.

How much does it cost to build an AI agent?

There is no fixed price for an AI agent — cost scales with the number of systems it needs to integrate with (payments, inventory, CRM, content pipelines) and whether it's built custom or assembled from existing tools. A single-purpose agent handling one workflow costs far less than a multi-agent system tied into a live commerce platform, like the storefront, UGC farm, SEO engine and agentic admin built together in Genium's eCommerce case study. Genium prices per scope after a scoping call rather than off a rate card.

How long does it take to build an AI agent?

Build time depends on scope: a narrow, single-task agent can take days to a few weeks, while a multi-agent system integrated across commerce, payments and content is a multi-month build. Genium's eCommerce case study involved several connected components — a bespoke React storefront with native payments, an AI UGC farm, an AI SEO engine and an agentic admin — which is a larger undertaking than deploying one standalone agent.

Can I build an AI agent without code?

Yes for simple, single-tool tasks — no-code and low-code platforms can produce a working basic agent quickly. Production agents that need to integrate with payments, inventory, CRM or multiple data sources generally require custom development for reliability and security at scale, which is why Genium's eCommerce build used a bespoke React storefront with native payment integration and a custom agentic admin rather than off-the-shelf no-code tools.