Agentic commerce, deployed inside your data boundary.

Where retail is going

The agentic commerce shift is real: shoppers are starting to ask agents to do things, not just retrieve answers. The retailers and marketplaces that win will be those whose product catalog, merchandising rules, and policies are accessible to agents — without giving every agent provider direct access to customer data.

We've published open research on agentic e-commerce and built the architecture pattern across multiple retail customers.

Where we focus

• Agentic commerce: conversational discovery, multi-turn shopping, agentic checkout
• Customer support: order-aware deflection, escalation, learning from resolutions
• Fraud and risk: transaction triage, ATO, chargeback automation
• Merchandising: pricing, assortment, demand forecasting
• Catalog quality: SKU enrichment, copy generation, image classification at scale

Compliance posture for retail

• PCI DSS-aligned. Payment data segregated; no payment context in model prompts.
• Customer PII redacted at the boundary. Names, addresses, and payment methods replaced with tokens before retrieval.
• Tenant isolation per business unit. Multi-banner retailers can isolate banner data while sharing platform infrastructure.

How we engage

Retailers typically begin with AI Feasibility & ROI when the question is portfolio-level: where to deploy AI first across commerce, supply chain, and customer support — and what each path will cost and return. If there's already a specific workflow ready to validate, they start with an AI Pilot instead. Custom AI Build and Private AI Deployment ship the production system, often integrating with existing commerce platforms (Shopify, Salesforce Commerce, custom).