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About OpenLens

We study language models. We built a way to track what they recommend.

We started OpenLens because the monitoring tools on the market didn't reflect how these systems actually work.

Why This Exists

Stop treating AI search like traditional search.

Traditional search is an index. You can browse through it, submit a site, and reliably show up. AI search is not browsable. You cannot submit your website to it. And yet, a majority of buyers already use it to decide what they purchase.

What you see with traditional search
  1. 1.Buyer types query into Google
  2. 2.Clicks through to your website
  3. 3.Analytics records the visit
  4. 4.Lead traced to source
You see every visit
Attribution is clear
Leads are traceable
What you miss with AI search
  1. 1.Buyer asks ChatGPT or an AI assistant
  2. 2.AI generates a recommendation
  3. 3.Buyer acts on the answer
  4. 4.You see none of it
No clickstream
No attribution
Evaluation invisible to you

Your existing tools were built for a system of pages and links. AI search generates recommendations and answers. You need new tools to see what these models are saying about the brands you manage. OpenLens was built for this.

Under the Hood

We open the apps. We run your prompt. We read what they say.

You are not checking a position on a page. When someone uses ChatGPT or Perplexity, they do not see ten blue links. They see an answer. Your client may be in it, or they may not. We monitor these answers: whether a brand appears, how it is described, and which competitors appear alongside it.

1

Query across platforms

We send your prompts to all four AI platforms via their official APIs. For platforms where the app experience differs from the API — ChatGPT, Perplexity, and Google AI — we also run automated browser sessions against the live app. This captures what users actually see, not just what the API returns.

2

Dual-validation extraction

Fast fuzzy matching detects brand names in each response. An AI parser then extracts structured context: sentiment, position, attributes, and citations.

3

Daily snapshot aggregation

Results are rolled into daily snapshots per brand, keyword, and platform. This creates a reliable time series. When your content changes, you can see exactly which models responded, and how.

The Team
CaltechGeorgia TechUniversity of Toronto

“The AI visibility space is filling up with tools built by people who noticed the trend and moved fast. We took a different route.”

The aibread.com team is composed of AI researchers from Caltech, Georgia Tech, and the University of Toronto who study language models. When these models became search engines, we tested every monitoring tool on the market. None of them reflected how these systems actually work — they applied old SEO thinking to a new kind of technology. So we built OpenLens.

There is no established playbook for AI visibility yet. We built OpenLens for the agencies writing it. You do the work. We prove it's working.

Start tracking AI visibility.

See what every major AI platform says about the brands you manage. Set up in under two minutes, no credit card required.