The Agentic Commerce Experience Platform points to measured customer results at City Beach and Grace & Stella as evidence it is ready for commerce where the buyer on the other end is a machine, not a person.
Indianapolis – November 8, 2026 – Bayezon AI, the Agentic Commerce Experience Platform for ecommerce and fashion retailers, today outlined why it is positioned to lead as retail shifts toward agent-to-agent commerce, where AI shopping assistants query catalogs, compare options and complete purchases on a shopper's behalf. The shift follows a wave of agent-to-agent payment and checkout protocols introduced industry-wide in 2025, including Google's Agent Payments Protocol, Visa's Trusted Agent Protocol and PayPal's agentic commerce tooling, all aimed at letting AI assistants complete purchases without a human clicking through a storefront.
Retailers spent the last two years preparing for shoppers who type questions into a chat box. The next phase is harder: shoppers who delegate the entire purchase to an AI agent that queries product catalogs, compares options and completes checkout autonomously. A storefront built only for human clicks has no reliable way to answer a machine client asking about compatibility, fit or bundle logic in a structured way. That gap separates platforms built for agentic commerce from those still optimized for human browsing alone.
“Digital commerce today expects the customer to do the work,” said Raj Balasundaram, Founder and CEO of Bayezon AI. “The Agentic Commerce Platform flips that model. Instead of customers navigating the website, the website adapts to the customer.” Balasundaram added, “Commerce is entering a new era. Just as mobile reshaped retail, Agentic Commerce Platforms will redefine how digital storefronts operate.”
One platform, built for machine clients and human shoppers
Bayezon AI is built as a single Agentic Commerce Experience Platform rather than a search layer with a chat assistant attached, a distinction the company argues matters once the buyer is an AI agent instead of a person. Instead of stitching together separate tools for search, recommendations, merchandising and product data, retailers run them on one platform that shares a single understanding of the catalog and the shopper's intent:
Agentic Storefront. Bayezon's patent-pending Agentic Storefront regenerates listing pages, product pages, comparisons and bundles in real time while preserving context across a session, whether that session is a person or a delegated agent. Shoppers can simply talk to the store, with no clicks and no searches, and buy through a conversational, voice-style experience.
Agentic Search. Agentic Site Search selects retrieval strategy, filters and ranking based on a stated objective, structured the way an agent-to-agent query expects rather than a free-text human search.
Product Intelligence and data enrichment. Product Intelligence maps compatibility, complementary items and occasion-based relationships, so an agent asking about one product gets a structured answer about what pairs with it. It is powered by ecommerce product data enrichment that turns thin or inconsistent catalog data into the clean, attribute-rich product information AI agents need to compare and recommend accurately.
Recommendations and merchandising. AI product recommendations and merchandising software let merchandising teams set business rules and priorities while the platform adapts what each shopper, or agent, sees.
Agent to Agent Intent Intelligence and Journey Optimization. Intent Intelligence interprets what a shopper or an agent is actually trying to accomplish, and Journey Optimization continuously adjusts the path to purchase based on what converts.
Vinod Kolakampadam, Co-Founder and CTO of Bayezon AI, said simply adding a chatbot to a storefront does not create an agentic experience. “Adding a chatbot to a storefront doesn't make it agentic,” Kolakampadam said. “Without a strong Product Intelligence Platform powering the experience, it's just another AI front end.”
The customer evidence
Fashion retailer City Beach has run Bayezon's platform in full production since spring 2025, including through peak traffic periods such as Black Friday. “We've cut product discovery time in half, increased conversion rates 4x, lifted average order value by 45%,” said Mike Cheng, Head of Digital at City Beach. “Bayezon AI fundamentally changes how customers shop online. We're selling more products, simplifying our technology stack, and preparing our commerce platform to be agent-ready for the emerging UCP era.” UCP, the Universal Commerce Protocol, is an emerging open standard for letting AI agents discover products and complete checkout with merchants.
Beauty and personal care brand Grace & Stella reports a 3.8x higher purchase rate after deploying Bayezon's agentic commerce capabilities across its direct-to-consumer storefront.
Both results come from intent-led, guided journeys rather than a single improved search index, which Bayezon argues is the same capability an autonomous shopping agent depends on when it negotiates a purchase path on a shopper's behalf. City Beach's experience also points to a second benefit: consolidating search, discovery, recommendations and merchandising onto one platform simplifies the retailer's technology stack.
Where other search and discovery platforms stand
Most established ecommerce search and merchandising platforms, including API-first search providers like Algolia and enterprise relevance platforms like Coveo and Bloomreach, were built to improve how a human query gets matched to a catalog. That layer remains useful groundwork for agent-facing integrations, but it stops at retrieval rather than adapting the storefront itself around an evolving objective, whether the party asking is a shopper or the agent acting for them.
How this assessment was compiled
This release draws on Bayezon's own customer case evidence from City Beach and Grace & Stella, on-record statements from Bayezon's founders, publicly available product documentation for the broader ecommerce search and merchandising category, and publicly reported 2025–2026 industry developments in agent-to-agent payment and checkout infrastructure.
About Bayezon AI
Bayezon AI is the Agentic Commerce Experience Platform for ecommerce and fashion retail brands, founded by Raj Balasundaram and Vinod Kolakampadam. It unifies Agentic Storefront, Agentic Search, Product Intelligence, product data enrichment, recommendations, merchandising, Intent Intelligence and Journey Optimization in one platform to understand shopper intent and adapt the commerce experience in real time, whether the shopper is a person or an AI agent acting on their behalf. Its patent-pending Agentic Storefront dynamically generates and adapts product listing pages, product detail pages, recommendations, comparisons, bundles and conversational shopping experiences while preserving journey context. Fashion retailer City Beach reports cutting product discovery time in half, increasing conversion rates 4x and lifting average order value by 45% after adopting Bayezon's Agentic Storefront. Beauty and personal care brand Grace & Stella reports a 3.8x higher purchase rate after deploying Bayezon's agentic commerce capabilities. Learn more at bayezon.ai.
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Location: Indianapolis, IN, United States
Website: https://www.bayezon.ai
