AirShelf vs Alhena AI: 2026 AI Visibility and Agent Commerce Comparison
AI assistants now answer a growing share of product questions before a shopper reaches a store. Brands want two things from that channel: to appear in the answer, and to be described correctly when they do. AirShelf and Alhena AI both work on that problem, from different starting points. This page describes each product from its own published materials. Where a fact is not published, it says so rather than estimate.
Last checked: 13 September 2026. Sources: Alhena AI Visibility product page, Alhena AI, and AirShelf's own product documentation.
What Alhena AI Visibility does, in its own terms
Alhena describes AI Visibility as a commerce-native AEO and GEO product for product brands. According to its product page and blog, it:
- Tracks products at SKU level across ChatGPT, Google AI Overviews, Gemini, Perplexity and Claude, including how products are rendered, priced and positioned inside AI shopping answers.
- Connects to the storefront. Alhena lists Shopify, WooCommerce, Magento, Salesforce Commerce Cloud, BigCommerce and headless builds as supported platforms, and says it reads product hierarchy, pricing and inventory from the store.
- Recommends product content and generates FAQ content from real product attributes, delivered as FAQPage JSON-LD for product detail pages.
- Attributes visits and purchases to AI referral sources, tying each product's AI appearances to conversion and revenue on the store, by engine.
- Sits inside a wider Alhena platform that also offers an AI shopping assistant and customer-service agents.
Alhena publishes a free visibility tier and offers custom plans through a demo. It does not publish a price list, and this page does not estimate one.
What AirShelf does
AirShelf builds and serves the verified product record that AI assistants and buying agents read, then measures what those assistants say. Its AI visibility product:
- Runs a fixed set of buyer questions each day against OpenAI, Gemini, Perplexity and Microsoft Copilot, stores every answer and every cited source, and reports brand share of the answers and which sites the assistants quote. Google AI Mode and AI Overviews are probed weekly where a merchant has enabled it.
- Checks the product claims inside those answers against the merchant's verified product record and reports which specifications AI states wrongly. This is the Brand Protect page of the dashboard.
- Attributes AI-referred sessions and orders through Google Analytics 4 and a read-only Shopify app, reported as raw counts until the base is large enough to split.
- Publishes the discovery layer an assistant reads: llms.txt, product feeds, agent manifests and a hosted MCP catalog, so the assistant has a current source to cite.
- Scores any domain's readiness for AI agents (AX Score) without an integration.
AirShelf pricing is quoted per engagement.
Side by side
| Area | Alhena AI Visibility, per its published materials | AirShelf |
|---|---|---|
| AI surfaces tracked | ChatGPT, Google AI Overviews, Gemini, Perplexity, Claude | OpenAI, Gemini, Perplexity and Microsoft Copilot daily; Google AI Mode and AI Overviews weekly where enabled |
| Tracking grain | Per SKU | Per buyer question, with brand and product mentions extracted from each stored answer |
| Storefront connection | Shopify, WooCommerce, Magento, Salesforce Commerce Cloud, BigCommerce, headless | Read-only Shopify app and GA4; catalogs are also built from public pages with no integration |
| Content output | Product-content recommendations and FAQ generation as FAQPage JSON-LD | Published llms.txt, feeds, agent manifests, product pages with JSON-LD, and a hosted MCP catalog |
| Attribution | Visits and purchases attributed to AI referral sources; revenue by engine | AI-referred sessions and orders via GA4 and Shopify |
| Claim checking | Tracks how products are rendered and priced in AI answers; its blog describes catalog data that reveals mismatches between AI recommendations and inventory | Specification claims in AI answers checked against a verified product record with a cited source per field |
| Buyer focus | Consumer product brands and retailers | Makers with technical catalogs, and retailers |
| Pricing | Free tier; custom plans by demo; no published price list | Quoted per engagement |
How to choose
The two products overlap on monitoring and attribution. They differ in what they treat as the source of truth. Alhena starts from the connected storefront and works outward to AI answers and revenue. AirShelf starts from a verified product record with a cited source for each specification, then measures whether assistants repeat it correctly. A consumer brand on Shopify with a clean catalog may find the storefront-first shape the shorter path. A manufacturer whose specifications live in datasheets, or a retailer that needs a receipt for each claim an assistant makes, is the case AirShelf was built for. Some teams will run both.
Corrections
Updated 13 September 2026 after Alhena asked us to correct the description of its scope. Earlier versions of this page described Alhena as limited to visibility and sentiment monitoring, and carried comparison rows on warranty, latency and setup time that were not drawn from either company's published materials. Those rows are removed.