How to Build an Agent-Ready Commerce Foundation

The shift from monolithic SaaS to task-specific agents mirrors the unbundling of software we saw en masse a decade ago. But AI accelerates the cycle: new models release monthly, and open-source variants improve weekly (sometimes even daily). The major tech ecosystems— Facebook, Google, Amazon, etc.—are launching innovative new consumer experiences which assist or fully complete the purchasing process at a rate that can be hard to even track, let alone implement.

With a breakneck baseline like that, enterprises that hard-wire vendor-specific SDKs or bake model names into business logic face endless refactors. Building from a foundation-first stance acknowledges that velocity is the norm, and allows organizations to create interfaces that anticipate churn rather than resist it.

Let’s take a look at what “foundation-first” means in action.

Foundation #1 – Prepare & Orchestrate Core Commerce APIs

A purchasing agent can’t assemble a compliant order without access to real-time services like discount logic, tax calculations, and inventory availability. If those live inside a legacy ERP and are only accessible through batch files, that’s a problem. And a sign you need to modernize.

Start by treating these core services as first-class products— designed for real-time access and built to serve both humans and agents:

• Pricing, promotions & discounts: rules, stacking logic, eligibility.
• Inventory: real-time availability, safety stock, back-order rules.
• Loyalty: point balances, tier benefits, redemption catalogs.
• Payments: tokenized methods, fraud scoring, capture/release workflows.
• Tax & duty: jurisdictional rules, exemptions, item classification.
• Catalog: variant relations, rich attributes, digital assets.

Each capability should be exposed through stateless, versioned APIs. Then, use an orchestration layer to compose those APIs into flows that reflect actual business use cases—like dynamic pricing, order validation, or inventory reservation.

These orchestrated flows should be made available as tools via a Model Context Protocol (MCP), or represented as specialized agents responsible for their specific domains. Any general-purpose agent can call those tools or collaborate with those agents to achieve higher-order goals—like building a draft order—without needing to manage the underlying logic.

Your commerce vendor or internal platform team should own and maintain these tools and specialized agents. The agents simply use them to get work done.

Foundation #2 – Build a Unified Knowledge Graph & Vector Search Layer

Agents don’t just transact, they reason. A support copilot retrieving warranty terms or a sales chatbot matching accessories to a laptop needs semantically rich context. That context isn’t buried in a single system—it’s spread across the business. So you need a way to unify and expose it.

Enter: the enterprise knowledge graph, mapping customers, products, content, and transactions into linked entities. Pair it with vector search, and agents can ask questions in natural language:

• “Show me winter jackets under $300 that ship before Friday.”
• “Has this customer ever returned a damaged item?”
• “Reorder this item when inventory drops below 20 items in stock”
• “What are the elements of this kit SKU and did we fulfill the order correctly?”
• “Does my new prescription interfere with any of my existing medications?”

Projects like Microsoft’s NLWeb will help further organize and expose this data to agents. However, it’s crucial to structure your public and private data properly so these systems can operate at peak performance.

Make both public and private knowledge accessible through permissioned APIs, so every agent—whether it’s a marketplace listing optimizer or an internal fraud detector—draws from the same trusted source of truth. Set policies like data masking, retention limits, and compliance rules at the system level, so you don’t have to rebuild them for every new agent. One set of rules, enforced everywhere.

Foundation #3 – Composable Orchestration & Governance

When multiple agents touch a single order—pricing, fraud detection, fulfillment, customer updates—coordination is mandatory. Event-driven workflow engines (like Temporal or AWS Step Functions) provide stateful choreography without entangling business logic. Layer on governance services to ensure you keep everything safe, measurable, and compliant:

• Trust & safety: filters to catch hallucinations, moderate risky content, and track who generated what
• Cost observability: tools to monitor agent usage, flag budget overruns, and visualize ROI across workflows
• Policy enforcement: controls like rate limiting, role-based access, and audit logs to stay compliant

To make this work at scale, design for hot-plug agents—ones that can be swapped in and out easily. Each agent registers what it can do (intent schema), when it's sure (confidence thresholds), and when to escalate (escalation paths). The orchestrator picks the right agent for the job, hands off the task, and steps in if confidence drops—logging every decision so the system keeps getting smarter.

How do you ensure agents don’t accidentally order 20,000 units of a SKU or issue $1 million in erroneous customer financing? Financial platform products from providers like Stripe or Adyen can help by delivering treasury and financial controls to govern agent transactions. These solutions enable you to define clear financial limits that agents must operate within. Emerging specialty vendors like Payman are also addressing this need, offering additional layers of protection and oversight.

Building with these foundational elements means setting your business up to adapt and evolve at whatever timeline you need.