AGENTIC COMMERCE OPTIMIZATION

A smarter catalog every day.

Win in Agentic Commerce with agentic optimization, human oversight, and continuous improvement.

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What's changing in commerce

Product discovery is no longer driven by people browsing pages.

AI shopping agents now evaluate product data directly to decide which products qualify, which get compared, and which are excluded entirely. These decisions happen upstream, before a shopper ever reaches a site or product page.

Legacy product catalogs were not built for this shift. This creates the need for a new optimization layer.

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What is Agentic Commerce Optimization?

Agentic Commerce Optimization (ACO) is the process of preparing your product catalog for AI-powered shopping experiences.

As agentic shopping engines like ChatGPT, Perplexity, Gemini, and Copilot surface products directly to consumers, they rely on structured, rich, and complete product data, not traditional PDPs or marketing pages.

ACO ensures your product information is ready for AI shopping agents to evaluate, compare, and recommend your products. It’s the foundation for winning visibility and conversion in AI-driven shopping.

What ReFiBuy does

ReFiBuy turns Agentic Commerce Optimization into an operating system for brands and retailers.

Our Commerce Intelligence Engine is an agentic-native, closed-loop platform designed to evaluate, generate, enrich, distribute, and monitor product catalogs for agentic commerce.

It is the operational system that enables digital teams to execute optimization continuously, not just measure it.

Those improvements are distributed across the systems AI agents rely on and continuously re-evaluated as discovery models, engines, and LLMs evolve.

EXPLORE THE PLATFORM

ReFiBuy operates as a closed-loop system:

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Ingest

Ingest product data across your catalog stack and normalize it at the SKU level so it’s ready for evaluation and automation.

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Evaluate

Evaluate how agentic shopping engines interpret your products by auditing catalog data and PDPs and flagging schema, crawlability, and content issues.

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Enrich

Enrich existing product data with more robust titles, descriptions, bullet points, and key features with human approval at every step.

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Distribute

Distribute optimized product data to agentic shopping engines where discovery, comparison, and selection decisions are made.

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Sync

Sync enriched product data back into your existing systems so improvements are applied without disrupting workflows.

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Monitor

Monitor how products perform across engines by measuring visibility, data quality, and competitiveness with clear, actionable results.

Who ReFiBuy is for

ReFiBuy is built for teams accountable for whether products qualify, appear, and perform in AI-driven discovery environments.

BRANDS

For brands managing large or complex product catalogs, where eligibility and visibility depend on consistent, interpretable data.

SEE HOW REFIBUY SUPPORTS BRANDS
RETAILERS

For retailers aggregating product data from many sources, where catalog quality and consistency directly determine discovery, comparison, and conversion.

SEE HOW REFIBUY SUPPORTS RETAILERS
AGENCIES

For agencies responsible for performance in modern discovery environments, where catalog issues often surface downstream but originate upstream in product data.

SEE HOW REFIBUY WORKS WITH AGENCIES
PARTNERS

For platforms, integrators, and technology partners building alongside AI-driven commerce systems and looking to extend catalog intelligence into their ecosystem.

EXPLORE PARTNERSHIPS

Why ReFiBuy

Most commerce tools optimize a surface. ReFiBuy optimizes the system underneath.

As AI shopping agents decide what products qualify to appear, product performance is determined by how data is structured, interpreted, and maintained across the stack, not by individual pages or channels.

ReFiBuy is built for that reality:

  • Agentic, closed-loop optimization, not one-time audits or enrichment passes

  • SKU-level eligibility, not aggregate scores or page metrics

  • Continuous adaptation, not static rules or checklists

  • System-wide visibility, not single-platform fixes

  • Agent-driven optimization with human control, not unchecked automation 

When AI agents decide what qualifies, optimization isn’t optional.

It has to be built into the system.

ReFiBuy's Commerce Intelligence Engine has accelerated our understanding of our readiness for Agentic Shopping experiences and how GenAI understands our product catalog.

President of US DTC & Global Digital, Steve Madden Josh Krepon
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Built by a team who has seen this shift before

ReFiBuy is built by industry leaders who have spent decades inside e-commerce, marketplaces, and product data infrastructure.

The platform reflects firsthand experience with how product data actually breaks across complex stacks, and why those failures surface too late for traditional tools to catch.

ReFiBuy was designed to solve a problem that legacy approaches were never built for: keeping product data interpretable and eligible as discovery shifts to AI shopping agents.

MEET THE TEAM

See how ReFiBuy works on real product data

The fastest way to understand ReFiBuy is to see how it evaluates, optimizes, and maintains product eligibility in an AI-driven discovery environment.

See how your catalog performs, and what changes when it’s built for agentic commerce. 

SEE REFIBUY WORK WITH REAL DATA