Agentic Commerce
Why this matters now
On some sites, a significant and growing share of traffic already comes from agents searching, comparing, and buying on behalf of people. It is a valuable customer journey that is easy to overlook.
Three things are happening at the same time:
- More buyer journeys begin in a conversational interface such as ChatGPT, Perplexity, Copilot, or Claude, and that share is rising.
- AI search increasingly recommends specific products inside its answer, so visibility now happens in the answer rather than the results page.
- Agents are starting to act directly, ordering and configuring without the buyer touching the interface at all.
A storefront, website, or app built for human clicks is not set up for any of these.
What an agent-ready commerce stack looks like
Catalogue and cart as APIs
Agents need to call catalogue, search, cart, pricing, promotion, and order as services with predictable, well-documented APIs. Some modern platforms, such as Shopify, expose these natively. Older or monolithic implementations usually do not.
A discovery surface that AI search can quote
Product pages with structured data, FAQ schema, canonical descriptions, an llms.txt file, and consistent entity identifiers, so AI search can cite the right product confidently and agents can resolve a query to a specific SKU.
Conversational entry points
Conversational interfaces on your own channels, plus integration with the third-party assistants buyers actually use, designed so the conversation can complete a transaction rather than route to a contact form.
AI-enriched product data at the source
Product information managed in a PIM with AI-driven enrichment, so attributes, descriptions, translations, and media are clean before they reach any channel, whether the audience is an agent or a person.
Trust, identity, and post-purchase
Agent identity and consent carried through orders, returns, and service, with an audit trail of what an agent did on a buyer’s behalf. This matters for chargebacks, fraud, and the EU AI Act.
How we approach a build
A typical engagement runs in clear stages:
- Audit: assess the agent-readiness of your current commerce stack across the layers above.
- Reference architecture: sized to your business and mapped against your current platforms.
- Key use cases: the highest-value agent journeys, such as pre-purchase research and configuration in B2B, or assistant-driven re-ordering in B2C.
- Production rollout: agents, integrations, observability, and governance.
- Measure and iterate: tracking how often AI search cites your products, how often agent interactions complete, and the cost per resolved interaction.
- Reporting: extending your insights, analytics, and BI reporting to cover agent journeys.
Why organisations work with us
End-to-end delivery
We combine advisory, architecture, implementation, and operational support in one collaboration model. What we recommend, we are able to deliver.
Composable commerce experience
We have deep experience in service-oriented and composable architecture for commerce, and we have contributed to composable patterns built for agentic and conversational experiences. We are a member of the MACH Alliance and work across commercetools, Shopify, BigCommerce, and other modern platforms.
Platform awareness
We track, test, and validate the platform, API, and agent capabilities of the technology vendors our clients rely on, so our recommendations reflect what these platforms can actually do today.
Technology-neutral approach
We do not develop our own foundation models. This keeps our advice independent on the fastest-moving part of the stack and lets us help you choose, integrate, and govern the technologies that best fit your needs.
Collaborative approach
We work closely with your teams throughout, keeping business goals, technology decisions, and operational realities aligned.
About Novicell
Novicell is a digital consultancy that helps organisations strengthen commerce, digital experience, and operational performance.
We work across strategy, platforms, architecture, development, marketing, and data, helping organisations integrate AI into their existing business and technology environments in a practical and measurable way. Our teams combine strategic advisory with hands-on implementation.
We work with heads of e-commerce, CTOs, heads of product, and digital leaders on both advisory and implementation engagements.
Whether agents are already showing up in your category or you are planning ahead, we help you assess where the opportunity is, design the architecture, and build and govern an agent-ready commerce stack.
Get in touch to discuss where agentic commerce can create value in your organisation.
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