AI Architecture Blueprint
What you take away
A reference architecture for agentic, AI-search-ready commerce, mapped against your current stack. It includes a prioritised list of gaps, a realistic sequencing plan, and a clear build-or-partner choice for each layer.
The result is a single document your leadership team can act on, and a practical basis for being ready for both conversational questions and search queries.
The blueprint works across seven layers of your architecture
Discovery surface
Structured product data, FAQ schema, an llms.txt file, and the conversational entry points that let AI agents discover, compare, and recommend your products. Most storefronts are currently invisible at this layer.
Catalogue and content as data
Product information (PIM), media (DAM), and content (CMS) treated as first-class data and exposed through clean APIs, with AI enrichment at the source so every channel inherits the same quality. This is what makes content ready for personalisation and conversational use at scale.
Composable commerce core
A MACH-aligned commerce layer, such as commercetools, BigCommerce, Shopify, DynamicWeb, or Adobe Commerce depending on context, that exposes catalogue, cart, pricing, promotion, and order as APIs the rest of your architecture, including agents, can call.
AI data supply chain
A fast, normalised data layer that brings together content, catalogue, customer signals, and inventory in one place, so storefronts, agents, and AI search all draw on the same source of truth. We often use Enterspeed at this layer.
Agent and orchestration layer
Agents that act across service, sales, search, and post-purchase, built on platforms such as Microsoft Copilot Studio, HubSpot Breeze, or custom Azure OpenAI solutions. Logging, evaluation, cost control, and the ability to switch an agent off are included by default.
Personalisation and customer data
A measurable personalisation layer grounded in a customer data platform or CRM, such as Raptor, Relewise, Salesforce, or Klaviyo. AI scoring is traceable to a real signal and connected to customer profiles and your systems of record, rather than operating as a black box.
Governance, identity, and observability
AI use mapped to identity and consent, carried through to every model call, so access stays compliant. Observability that lets you see what an agent or person did, why, and at which step of the customer journey.
How the engagement runs
A blueprint engagement usually runs over about four weeks, in three stages:
Current-state map
We map your current stack against the seven layers above, identifying what is in place, what is missing, and where you are exposed, including data risks, unsupported platforms, gaps in governance, and fragile integrations.
Reference architecture and gap analysis
We produce a reference architecture sized to your business, with a gap analysis and prioritised investments sequenced realistically against your other roadmap commitments.
Sign-off and next steps
A workshop with your leadership team to finalise the blueprint and agree the next two or three concrete build engagements, or the right partner to deliver them.
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 are a member of the MACH Alliance and have contributed to composable commerce patterns designed for AI-assisted and conversational experiences. We work across modern commerce, CMS, and martech ecosystems, and we are a HubSpot Diamond Partner, a Klaviyo Gold Partner, and a commercetools partner.
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.
Business-focused implementation
Our focus is on measurable outcomes, operational adoption, and long-term maintainability, rather than experimentation without clear ownership.
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 CIOs, CTOs, heads of e-commerce, and heads of architecture on both advisory and implementation engagements.
If it helps, we can start with a short architecture conversation: we will walk you through our reference architecture, ask the questions that matter, and give you an honest view of whether a full blueprint engagement is the right next step. No preparation needed on your side.
Get in touch to discuss where AI can create value in your commerce architecture.
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