AI-Native Conversational Buying 

Complex B2B catalogs, variant-heavy SKUs, and contract pricing structures create friction that traditional ecommerce search can't solve. Procurement buyers remember last week's order, not the SKU number—a challenge that defines conversational commerce B2B at its core.

They think in operational terms—approximate descriptions, previous purchases, rough specs—not catalog identifiers. The result is ordering errors, rep dependency for what should be self-service, and lost efficiency across high-volume procurement workflows—exactly the inefficiencies AI-powered procurement is designed to eliminate.

Conversational Buying bridges the gap between how buyers think and how systems are built.

AI conversational ordering for B2B works simply: buyers type what they need in plain language—the way they'd talk to a sales rep—and the system resolves history, variants, pricing, and cart in one step. 

A procurement buyer types: I need 50 of those 1-inch carriage bolts we ordered last week, but get me the 1-1/4-inch version instead.

The system does the rest:

1. Resolves the historical order reference: no order number, no date, no SKU required.
2. Identifies the original product and product family: from order history and account context.
3. Detects the variant substitution: size swap recognized from plain language.
4. Maps to the correct catalog SKU: even across inconsistent supplier naming.
5. Applies negotiated contract pricing: automatically, for that account.
6. Pre-populates an editable cart: ready to review and submit.

Here is what the buyer doesn’t have to do manually:

• Navigate catalog 
• Look up SKUs
• Check pricing

One request, one cart. 

• Conversational Order Resolution: Buyers reference orders the way they remember them (last week's order, the pending invoice, what I usually get). The AI resolves ambiguous references using order history, purchasing patterns, and account context, without exact identifiers required.
• Intelligent Variant & Product Family Matching: The system understands relationships between SKUs within the same product family. Buyers can swap sizes, materials, pack sizes, or capacities in plain language—AI will identify the correct substitution, flag unavailability, and suggest the closest match when needed.
• Multi-Line Orders from a Single Request: Complex procurement requests don't need to be broken into multiple steps. A single conversational message can generate a complete, multi-line cart—including quantity adjustments, variant swaps, and pricing applied across all lines.
• Context-Aware Cart Automation: The assistant acts directly on the commerce workflow. It pre-populates carts, applies negotiated contract pricing, respects account permissions and organizational buying rules, and supports approval workflows. All generated lines remain fully editable before submission.
• Multi-Turn Dialogue: Buyers refine orders through natural conversation—adjusting quantities, swapping variants, adding complementary items, or removing lines—before proceeding to checkout. No need to formulate a perfect request upfront.
• Graceful Ambiguity Handling: When a request is ambiguous—multiple matching products, unclear order references, unavailable variants—the assistant explains the uncertainty, presents options, and guides the buyer toward resolution rather than producing an incorrect result.

• Industrial Distribution & Manufacturing: 
  A procurement manager reorders fasteners, components, or maintenance supplies on a weekly cycle. They remember previous orders and approximate specs (not catalog codes). Conversational Buying resolves their intent directly, applies contract pricing, and builds an accurate cart without a single catalog click.
• Wholesale & Multi-Entity Procurement:
  Enterprise buyers managing orders across multiple cost centers or legal entities can place complex, multi-line orders through conversation—with organizational rules, approval workflows, and account-specific assortments applied automatically.
• Aftermarket & Parts Distribution: 
  Buyers sourcing replacement parts often reference what was previously installed, not what's in the catalog. The AI resolves historical orders, identifies the product family, handles variant substitution (grade, size, specification), and flags compatibility issues before checkout.

• Faster repeat ordering: No catalog navigation required.
• Fewer ordering errors: From SKU guesswork or manual entry.
• Lower dependence on sales reps: Boost of self-service transactions.
• Higher self-service adoption: Across catalogs of any complexity.
• Scalable digital ordering: For multi-entity and high-volume procurement.
   

Conversational buying reduces the distance between procurement intent and confirmed order—the foundation of scalable B2B order automation every buyer, catalog, and contract.

Most AI ordering tools are built on proprietary integrations—wired to a single model, interface, or vendor's ecosystem. Virto's conversational buying is built differently.

The architecture connects any AI agent or automation system to Virto's commerce operations through an open, standardized protocol layer—meaning the conversational interface, the pricing engine, the catalog, and the cart all work together without custom integration work per use case. Swap the AI model, add a new procurement automation tool, or connect an enterprise copilot—the commerce layer doesn't need to be rebuilt each time.

This is possible because Virto implements MCP Commerce (Model Context Protocol), an open standard developed by the Commerce Operations Foundation (COF) that defines how AI agents invoke commerce capabilities. 

Virto has contributed both a production adapter and improvements to the COF reference server—an active participant in the standard, not just a consumer of it.

How the protocol layer works (for technical evaluators):

• AI Agent: The conversational interface that receives buyer intent in natural language.
• MCP Protocol Layer: Standardizes how agents discover and invoke commerce. capabilities (product search, cart creation, pricing retrieval, order submission).
• MCP Server: The runtime that hosts and routes tool calls from agents to the platform.
• Virto Commerce Adapter: Translates MCP tool calls into native Virto API requests and returns structured responses.

Practical outcome: No proprietary lock-in to a single AI provider, no point-to-point integrations that break with every release, and a foundation that stays current as AI tooling evolves.

AI-Native Conversational Buying is part of Virto's AI ecommerce platform for B2B—designed so each capability works independently or together across the buying journey:

• AI Product Assistant: Answers product questions on the product page before the buyer commits.
• Smart PO to Order Capture: Converts uploaded purchase orders into structured orders automatically.
• Virto OZ: The back-office AI agent orchestrator for operational commerce workflows.
• Intent Search: Surfaces the right products from natural language queries.

As a conversational buying platform built on open standards, it connects to the rest of the AI layer without proprietary lock-in.