Key Takeaways
- Chicago-based Lantern announced on July 1, 2026 an Agentic Commerce platform that measures how products surface inside AI shopping experiences and executes fixes, defining a new category it calls "Agentic Commerce Performance"
- Founder Andrew Lissimore built Headphones.com through SEO, then watched ChatGPT ignore his products entirely. That experience drove Lantern's pivot from loyalty tools to GEO (generative engine optimization), backed by a $3.1 million seed round led by Salesforce Ventures
- The GEO market is heating up fast, with Profound reaching unicorn status. Lantern differentiates through ecommerce-only, product-level analysis — and for ecommerce operators, measuring how AI evaluates their products and cleaning up product data are becoming urgent tasks
Lantern Announces a New Platform for AI Shopping Optimization
Lantern launched a loyalty tool for e-commerce brands. Now, it's doubling down on AI GEO and LLM result optimization. Read its pitch deck.
www.businessinsider.comOn July 1, 2026, Chicago-based startup Lantern officially launched a platform that measures how ecommerce brands' products appear inside AI-powered shopping experiences and carries out improvements. According to the press release, AI-driven ecommerce traffic is up 4,700 percent year over year, and roughly 75 percent of new product searches now happen inside large language models. That traffic converts at 5 to 8 times the rate of Google organic search, yet 60 percent of those interactions end without a click.
When the starting point of shopping shifts from a list of links to an AI answer, a product that goes unnamed in that answer might as well not exist to customers. That is the problem Lantern sets out to solve. Its platform makes visible how AI systems interpret a brand's products, identifies what is limiting visibility, and applies fixes to product pages and catalogs with team approval.
AI agents decide what gets recommended, and most brands have no idea how they're being evaluated. The playbook brands relied on for the last decade doesn't carry over. Lantern doesn't just show you the problem. It fixes it.
Source: Andrew Lissimore, CEO of Lantern
Why an SEO Success Story Pivoted from Loyalty Tools to GEO
Understanding Lantern's announcement requires knowing the founder's background and the pivot behind it. As Lissimore told Business Insider, he built the audio equipment retailer Headphones.com into one of the most trusted names in the industry by mastering SEO. But when ChatGPT emerged and he asked it about his own products, the answers made no reference to his company at all. That experience convinced him this is "the most important transition since search."
Lantern was originally founded in 2024 to help ecommerce brands with customer loyalty. Its co-founders include Kyle Peatt and Dominic McPhee, the former Shopify designers who built the Polaris design system. According to TechCrunch, the company raised a $3.1 million seed round led by Salesforce Ventures in 2025, with participation from Sidekick Partners and Day One Ventures.
Over the following year, the company shifted its center of gravity toward AI recommendation optimization. It hired ex-Amazon engineers and trained a proprietary internal model that predicts how a brand's products will appear in AI-powered queries. Pricing starts at 99 dollars a month, with custom pricing for enterprise clients. Per Business Insider, Lantern is raising additional capital to expand technical talent and distribution. This launch presents that pivot to the world under a new banner: Agentic Commerce Performance.
A Design That Goes Beyond Measurement — and What Is Inside
Agentic Commerce Performance, as Lantern defines it, covers three stages of how products fare inside AI shopping: whether they get Surfaced, Selected, and Converted. The platform's key capabilities are as follows.
| Capability | What it does |
|---|---|
| Agent Ready Score | Scores how prepared a store is for AI-driven commerce |
| AI Visibility Tracking | Tracks how often products and brands appear across AI-generated answers |
| Product-Level Analysis | Identifies the specific issues limiting how each product is interpreted and recommended |
| Category Benchmarking | Compares performance against competing products and brands |
| Automated Fixes | Applies prioritized changes across product pages and catalogs, with team approval |
What the company emphasizes as its difference from conventional ecommerce tools is that it executes fixes rather than stopping at reporting. Teams of specialized agents run on Lantern's proprietary model, continuously monitoring and improving how products appear across AI systems. It is not a dashboard for staring at problems but a product whose scope extends to proposing changes and deploying them after approval. Supported platforms include Shopify, BigCommerce, WooCommerce, and Adobe Commerce.
Its involvement in standardization is worth noting. Lantern states that it contributes to emerging protocols for how agents discover products and complete transactions, including the Universal Commerce Protocol (UCP) backed by Google and the Agentic Commerce Protocol (ACP) from OpenAI and Stripe. In a market where models, retrieval methods, and protocols remain unsettled, the design philosophy is to be the side that adapts to change.
Competing in a GEO Market That Already Has a Unicorn
The GEO and AI visibility market Lantern is entering has become fiercely competitive over the past year. Front-runner Profound raised a $96 million Series C at a $1 billion valuation, reaching unicorn status with enterprise customers like MongoDB and Figma. The field is diverse: AthenaHQ, founded by former Google Search engineers; Jasper, entering from marketing AI; and Daydream, an SEO agency that raised $15 million.
Lissimore's differentiation in this crowded field is straightforward: staying focused purely on ecommerce. While many GEO tools address overall brand visibility, what niche ecommerce sellers really want to know is how individual products are treated relative to niche competitors. Lantern concentrates on product-level analysis and in-category benchmarking.
Its investor materials cite figures that underscore the market shift. A 2025 Pew Research study found that when an AI summary appears in search results, only 8 percent of users click a conventional result, down from 15 percent without one. Adobe's 2026 data shows shoppers arriving through AI answers convert 31 percent higher. One analysis found only 38 percent of pages cited by AI still rank in the top ten search results, suggesting that search ranking and AI recommendation are splitting into separate competitions.
What This Means for Ecommerce Operators
There are three points ecommerce operators should take from this news.
First, knowing where you stand is the starting point. When you ask ChatGPT, Perplexity, or Gemini about your main product category, does your brand get named, or do competitors get picked instead? As Lissimore's own experience shows, brands with strong SEO track records are structurally the least likely to notice the gap between search rankings and AI answers. The very emergence of metrics like the Agent Ready Score speaks to the scale of this measurement need.
Second, the substance of any countermeasure comes down to product data. As Lantern's capability list shows, what determines AI visibility is product page copy, catalog structure, and the accuracy of attribute data. This is continuous with the data readiness problem repeatedly raised across Agentic Commerce, and it overlaps with supporting protocols like UCP and ACP. Rather than treating GEO as a special campaign, it is more realistic to treat it as the ongoing work of structuring product information to be read by machines.
Third, tool adoption should factor in the limits of effectiveness measurement. An industry-wide challenge for GEO is that no rigorous method yet exists to isolate the link between an intervention, changes in AI recommendations, and revenue impact. With behavior varying across models, the practical stance is to avoid taking any single tool's numbers at face value, start small, and validate against your own data. The 99-dollar monthly price point lowers the barrier to exactly that kind of trial.
Conclusion
Lantern's announcement is one startup's product launch, but it also signals that "how AI evaluates you" is becoming an independent operational discipline for ecommerce. The fact that an operator who won through SEO acknowledged the limits of that playbook and bet on product-level AI optimization symbolizes a market turning point. Whether the category name Agentic Commerce Performance sticks remains to be seen, but the underlying demand — measuring and improving each stage of how products get surfaced, selected, and converted by AI — is certain to grow. Alongside protocol standardization, this is a space worth watching closely.
