The single 0 to 100 number measuring how ready your store is for AI understanding. Every store Atom Foundry scans receives one.
AI needs one comparable number before it can reliably read and evaluate any merchant at all. Without it, AI has no way to compare a store against competitors, so it defaults to skipping it.
A beauty brand scores 38. The scan reveals missing trust signals and JavaScript-rendered prices AI cannot read. Fixing both moves the score to 61 and makes the store legible to AI again.
Every scan runs the same sequence, left to right. Hover a step to see why AI weighs it the way it does.
AI vision systems read product images directly. A mismatched alt tag makes a photo invisible to the AI brain even though the AI eye can see it fine.
Structured data is the primary language AI agents use to understand what a store sells, at what price, and how trustworthy it is.
A technically broken store is an invisible store. Blocked crawlers and slow pages break AI navigation before content is ever read.
AI agents run a machine-readable trust check before routing a buyer or completing a purchase, not a design check.
AI agents are starting to complete purchases, so a wrong price or stock status breaks the transaction and the trust that comes with it.
AI agents match stores to specific buyer intent, not keywords. Generic copy cannot match a specific request.
There is a real difference between a store AI mentions and a store AI trusts enough to recommend first. This factor measures one narrow signal, verifiable social proof, not the store's overall Recommendation Confidence, which is the broader outcome all 8 factors build toward.
A brand with no mentions or citations outside its own channels is treated as unverified by AI systems trained on the wider internet.
Picture a production line. The store enters on one side. Every layer runs its own inspection. A score comes out the other end.
This is the same weighted math AI runs on every scan. Drag any factor and the overall score recomputes live.
The same buyer question gets a different AI read depending only on the score.
Eight strands, one for each factor. Together they form the store's AI Commerce DNA.
Strip away the terminology and this is what AI is actually asking, every time it opens a store.
No long explanations. Just the read AI gets on every factor, at a glance.
Two stores selling the same category, one AI reads with far more confidence than the other.
Click through four real fixes in order. Watch the score, and the verdict, change with every one.
Every scan is a cell. Click one to see the date and the score it produced. A single snapshot is a moment. A timeline is a trend.
A score below 50 means AI systems are actively skipping the store in recommendation flows. A score above 85 means AI agents can confidently recommend it, and very few stores in the Atom Foundry database have reached that threshold so far.
The fastest gains usually come from the heaviest-weighted layers: AI Structured Signals, Core Technical, AI Trust, and Commerce & Feed Accuracy each carry 15% of the score. Fixing missing schema, a broken trust signal, or an inaccurate price moves the number quickly.
A beauty brand scored 38. The scan found missing trust signals and JavaScript-rendered prices AI could not read. Fixing both moved the score to 61 and brought the store back into AI recommendation flows.
The score is built from 8 measurement layers benchmarked across 66,090 scanned stores, weighted by how much each layer changes AI recommendation behavior. Full methodology and thresholds are published on the Methodology page.
Run a live scan and get the same 8-layer breakdown shown on this page, built from your store's actual signals.
Check My Store's Score →Illustrative example · single-site signal for atomfoundry.dev.
View full signals →