See what every AI agent is evaluating in your store.
Shoppers are asking ChatGPT, Claude, and Perplexity for product recommendations carrying exactly what they want — budget, features, urgency, competitive context. Every agent that visits your catalog arrives with that intent baked in. Most merchants never see any of it.
Your analytics see a page view. The agent already knows what the shopper wants.
A customer tells ChatGPT exactly what they're looking for: budget, brand preferences, specific features, use case. That intent rides with the agent into your store. Your analytics show a hit on a product page. That's it.
The conversation that shaped their decision is already over by the time they arrive. The richest shopping signal on the web today is flowing through your store — and you can't see any of it.
- Budget: $60–$100
- Feature: bass priority
- Use case: running
- Compared: 3 brands
- Platform: ChatGPT
- Urgency: this week
- /products/earbuds
- Duration: 0:23
- Bounced
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Three systems turn invisible agent traffic into structured intent.
Detection at the edge. Classification against your catalog. A graph that compounds with every visit.
A shopper asks for earbuds. Here's what lands in your Intent Graph.
A shopper tells ChatGPT: "Find me wireless earbuds under $100 with good bass for running."
ChatGPT visits your product pages to evaluate. In under 5ms, your edge layer fingerprints the agent, classifies the intent, and writes a structured signal to your Intent Graph.
That intent signal is now yours to act on — in your AI agent responses, your pricing strategy, your re-activation audiences. Every agent visit adds another signal. The graph compounds.
{ "platform": "chatgpt", "category": "wireless_earbuds", "budget": { "low": 60, "high": 100, "currency": "USD" }, "feature_priority": ["bass", "battery"], "use_case": "running", "compared_against": 3, "urgency": "this_week", "attribution_fp": "af_7C•••", "detection_ms": 4.1 }
Built from every agent visit. Richer every day.
Your graph doesn't just log visits — it builds a living map of what your customers want. Which products agents evaluate most. Which price points win. Which features drive recommendations. Which competitors appear in the comparison set.
Every dimension is structured, queryable, and automatically wired into every other system — your AI agent responses, your content optimization, your re-activation audiences.
Six merchant outcomes from one intent layer.
See what agents ask your store
Every query, every budget range, every feature priority — the questions shoppers are really asking AI agents about your category, surfaced in one place.
Map pricing sensitivity
Understand how price points cluster by shopper segment, which ranges win comparisons, and where your catalog is over- or under-priced vs. agent-expected bands.
Identify competitive blind spots
See who agents compare you against, on which dimensions. Find the feature, positioning, or price gap where you're losing recommendations.
Build compounding intelligence
Every visit enriches the graph. Your intent intelligence grows while competitors start from zero.
Track feature-level wins
Know which product attributes drive recommendations on ChatGPT vs. Gemini vs. Rufus — each platform weighs differently, your graph captures each.
Feed every downstream system
Intent data automatically powers your AI agent responses, your content optimization, and your re-activation campaigns. One capture, three downstream wins.
Start capturing the intent you're missing.
See what AI agents are really asking about your store. Every query, every budget, every comparison — in one place, live.