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Latest updates and insights from ORBEXA

Engineering

An AI Agent Recommended Your Out-of-Stock Product. It Will Not Come Back.

When an AI shopping agent recommends a product that turns out to be unavailable, it does not shrug and try again. It deprioritizes that merchant's data in future queries. One stale inventory entry can cost you months of AI agent trust. Real-time synchronization is not a premium feature — it is damage prevention.

Engineering

The $0 Investment That Makes Your Products 3.4x More Visible to AI Agents

Princeton and Stanford researchers found that GPT-4 achieves 54% accuracy on structured commerce data versus just 16% on unstructured HTML — a 3.4x improvement from data formatting alone. Schema.org JSON-LD is the format. Here is exactly how to implement it.

Engineering

From Product Pages to Knowledge Graphs: Making Your Store AI-Discoverable

An AI agent tasked with finding the best wireless noise-cancelling headphones under $300 faces a fundamental challenge. It does not see the web the way a human does.

Engineering

The Data Flywheel: How ORBEXA Continuously Improves Commerce Data Quality

Every conversation about AI agents in commerce eventually runs into the same wall: data quality. According to industry research, approximately 80% of the engineering work required to deploy AI agents in production is data engineering -- cleaning, normalizing, validating, and enriching the information that agents consume.