July 2025 - atronous

The world of shopping is undergoing a seismic transformation. It is not just how people buy — it is who (or what) is buying that is changing. We are rapidly moving from an internet designed for humans to an ecosystem optimized for AI agents. Welcome to the era of agentic AI shopping where bots, not browsers, drive transactions.

The Shift: From Human-Centric to Agent-Centric Commerce

For decades, e-commerce has revolved around humans: rich product descriptions, lifestyle images, curated filters. But tomorrow’s consumers will not just be people — they will be intelligent agents.

These agents do not scroll. They compute.

Instead of reading a product description like:
“A cozy fall cardigan in rich burgundy…”

they need structured data like:

Color: Burgundy
Delivery: 2 days
Rating: 4.7

Voice-enabled prompts, zero-click checkouts, and agent-to-agent (A2A) negotiations are reshaping how products are discovered, evaluated, and purchased. This is not science fiction, it is happening now, led by platforms like OpenAI’s ChatGPT, Google’s Gemini, and Anthropic’s Claude, all aligning behind Model Context Protocol (MCP) standards that enable seamless A2A commerce.

So, what is A2A Commerce?

A2A (Agent-to-Agent) commerce refers to digital shopping interactions where two intelligent agents, one representing the buyer and the other the seller communicate, validate, and transact autonomously. These agents are powered by advanced language models and multimodal reasoning engines that negotiate and decide on behalf of users.

In this new ecosystem:

Agents demand structured, machine-readable data.
Subjective or unstructured product pages are ignored.
Success hinges on how computable your product catalog is.

Where atronous.ai Fits In: Your Translation Layer to the Agent World

At atronous, we are building the infrastructure that connects today’s brands with tomorrow’s AI agents.

We have engineered the industry’s first Golden Catalog for A2A commerce — a framework that transforms human-written product data into agent-computable content that is compliant with emerging MCP and A2A standards.

Our core capabilities:

Audit & Agent-Readiness Scoring: Evaluate how well your current listings perform with AI agents like ChatGPT, Gemini, Claude, and others.
PDP-to-MCP Conversion: Convert descriptive product detail pages (PDPs) into structured, machine-readable formats compliant with OpenAI, Google, and Anthropic protocols.
Missing Field Detection: Identify and fill critical gaps agents need — such as variants, dimensions, delivery dates, compliance attributes, and more.
Agent-Optimized Publishing: Syndicate data not just to marketplaces like Amazon and Shopify, but to emerging AI shopping agents that will dominate the future.

In short: we make your products computable.

Why This Matters

In an AI-first commerce world, visibility = structure. If your product cannot be interpreted by an agent, it will not be shown, selected, or sold. That means lost conversions, slower velocity, and fewer brand impressions.

Imagine:

A buyer tells their shopping assistant, “Find me a non-toxic kids’ chair under $100 that ships in 2 days.”
The agent scans millions of SKUs but skips your product because it lacks structured tags for safety or delivery time.

This is the new SEO. And at atronous, we ensure you are not left behind.

The Future is Agentic. Are You Ready?

We are entering a world where agents shop along with people. And in that world, brands will need new playbooks, new catalogs, and new infrastructure to win.

At atronous.ai, we are proud to be leading that charge not just adapting to the agentic future, but building it.

Let us help your brand show up, get picked, and get sold whether the buyer is a person or an AI agent.

Taxonomy originated from Greek, and the word “taxis” means organization or arrangement.

Product taxonomy involves categorizing your products by type (think Shoes, Home, Electronics, Arts & Crafts etc) to enhance user navigation within your product catalog. It serves as a method for structuring all items on your e-commerce platform.

It makes sense to taxonomize products so that customers who like to browse online, are able to find what they’re looking for.

Where taxonomy becomes challenging for companies to manage include:

Taxonomizing large supplier catalogs to match a retailer’s taxonomy.
All retailers all have different taxonomies.
Taxonomies change over time requiring retroactive updating.

Let’s break these down further:

Taxonomizing large supplier catalogs to match a retailer’s taxonomy

A distributor with many categories will have to know how each product fits into a retailers taxonomy for product content template completion.

This involves a review of each product and then manually checking the retailer’s site for where those products fit.

Our customers have shared that the task to label 6,000 products across 110 different categories, would be manual, likely done in a spreadsheet and take a week or two to complete (best case).

All retailers all have different taxonomies.

If you’re a brand, distributor or manufacturer with products that span many categories, it can become difficult to label your products with the appropriate category of your various retailer/marketplace partners.

As an example, BestBuy, Costco, Target and Amazon have variations in their taxonomies.

Amazon – Electronics/Televisions & Video

BestBuy – TV & HomeTheatre.

Target – Electronics/TVs & HomeTheatre

Costco – Home/Electronics/TVs

If you’re adding your television products to twenty retailers, you will have to know which taxonomy that they use, and then repeat the process for each retailer which can take weeks to complete.

Taxonomies change over time requiring retroactive updating.

As assortments build over time, so do the taxonomies. You may start with a category like Footwear and when you have enough product density, start expanding beyond men’s and women’s. For example, you may need slippers, boots, sandals, athleisure, runners etc.

The problem here is that when you add a new classification, you need to ensure that you re-label products into the best category. If you don’t, customers who browse your site may not find what they’re looking for. The impact could be lost sales, leading to overstock of clearance for those lost SKUs, a potentially huge financial risk.

How Atronous’s AI tackles taxonomy

Atronous’s AI agent takes the burden off of teams from having to manually map retailer taxonomy to supplied products.

Our AI learns the supplied products via artifacts like images, part numbers and text descriptions, then learns the taxonomy of the retailer partner.

Once AI training is complete, it begins to write the retailers taxonomy onto your csv template so that you can review and approve.

If the AI predicts that a product doesn’t fit into any of the retailer’s taxonomy, it will highlight those products to you for further inspection.

How our AI technology stack operates can be found here – https://atronous.ai/schematic-extraction-v0-1-0-architecture-enhancements-and-future-work/

The Results:

Atronous’s AI was put to the test recently to build a custom taxonomy for over 57,000 SKUs for a client. Atronous achieved 98.7% classification accuracy and reduced product onboarding time by 70%. By consolidating 200+ attributes into standardized templates and enriching missing data using AI, atronous enabled faster, more accurate listings across Shopify, Amazon, and other channels. This led to 5x faster listing velocity for long-tail products, improved SEO, and enhanced internal search and filtering. The solution now serves as the foundation for scalable catalog growth and marketplace compliance.

Month: July 2025

Commerce Meets Intelligence: Agentic AI Shopping and the Golden Catalog Infrastructure