Prepare your commerce engine for multi-interface and AI-driven discovery
TMO helps brands structure the product data, content, feeds, governance, APIs, and measurement foundations needed for their products to be discovered, understood, and recommended across search engines, marketplaces, social channels, AI assistants, and emerging commerce interfaces.
TMO helps brands structure the product data, content, feeds, governance, APIs, and measurement foundations needed for their products to be discovered, understood, and recommended across search engines, marketplaces, social channels, AI assistants, and emerging commerce interfaces.
Benchmark how your brand and products appear across AI-mediated discovery and identify the most obvious visibility gaps.
TYPICAL DELIVERY
Assess your system and catalog architecture to determine which AI capabilities are feasible now, what is missing, and what needs to change before implementation.
TYPICAL DELIVERY
Build and deploy AI commerce features alongside the data, content, integrations, and measurement foundations they depend on.
TYPICAL DELIVERY
Continuously improve AI visibility, content quality, feed performance, and competitive positioning as channels evolve.
TYPICAL DELIVERY
The Intelligence Layer for Modern Commerce
For systems to operate effectively across these environments, information must be more than visible to people. It must also be structured, machine-readable, accurate, governed, and available to external systems.
System-First Architecture
Capabilities are built as structured, modular systems that extend beyond any single storefront, channel, or platform.
Unified Commerce Data Layer
Product knowledge, customer signals, and transaction data are structured for AI consumption, governance, and accessibility.
Build the Foundations Behind
Multi-Interface Commerce
Make products easier to interpret, compare, and recommend. Expose accurate product, inventory, price, and policy information through structured formats.
Improve how products and brand information are exposed across traditional and AI-mediated discovery channels.
Define how commerce systems and AI interfaces should interpret, present, and act on business information.
Make commerce information accessible to websites, marketplaces, social platforms, assistants, and future channels through shared data architecture, APIs, adapters, and system integrations.
Measure whether AI channels and interfaces are accurately representing the brand and contributing to commercial outcomes.
Make products easier to interpret, compare, and recommend. Expose accurate product, inventory, price, and policy information through structured formats.
Improve how products and brand information are exposed across traditional and AI-mediated discovery channels.
Define how commerce systems and AI interfaces should interpret, present, and act on business information.
Make commerce information accessible to websites, marketplaces, social platforms, assistants, and future channels through shared data architecture, APIs, adapters, and system integrations.
Measure whether AI channels and interfaces are accurately representing the brand and contributing to commercial outcomes.
Not primarily. TMO can work across Shopify Plus, Adobe Commerce (Magento), headless, and other commerce architectures. AI readiness depends more on whether product information, pricing, inventory, policies, feeds, APIs, and measurement are structured and accessible to the systems that need them.
GEO (Generative Engine Optimization) focuses on improving how content and brand information can be understood and surfaced by generative search systems. AI search visibility describes how often and how accurately a brand or its products appear in AI-generated answers and recommendations. AI commerce readiness is broader, covering the data, content, feeds, APIs, governance, and measurement foundations needed to support AI-driven discovery and commerce.
Improving AI visibility starts with understanding where and how the brand currently appears, then addressing gaps in content clarity, product information, structured data, schema, feeds, technical accessibility, and authority signals. TMO can benchmark priority prompts and competitors, identify visibility gaps, and build a roadmap for ongoing GEO and AI discovery optimization.
AI systems need reliable, machine-readable information to understand products and compare attributes such as price, availability, specifications, compatibility, variants, and policies. Product schema, merchant feeds, and well-structured catalog data make this information easier for search engines, shopping platforms, and AI assistants to interpret and use consistently.
A readiness assessment examines the foundations required for AI-driven discovery and commerce, including product data and taxonomy, structured content, schema, merchant feeds, APIs and integrations, governance, technical accessibility, analytics, and AI-referral measurement. The goal is to identify what is already usable, what is missing, and what should be prioritized before implementation.
Preparing for agentic commerce requires making key commerce capabilities available beyond the website itself. This includes structured product knowledge, reliable pricing and inventory data, accessible APIs, transaction and fulfilment services, permission controls, governance, and measurement so AI assistants and other interfaces can safely discover products, support decisions, and eventually interact with commerce workflows.
