AI Visibility

Finally, AI visibility built for the enterprise

Get thousands of buyer questions, run natively in every engine, country and market you sell in, analyzed and translated into actionable insights. So your brands get cited and recommended by AI.

The Brandlight dashboard for Adidas: a visibility score of 54.24% charted over time, and a visibility ranking led by Nike Air, Adidas Ultraboost and Puma Deviate Nitro.

Trusted by Global CMOs & Fortune 500 Brands

Our Platform

Complete AI visibility infrastructure
for global brands.

One connected process that goes from real questions to answers you can act on.

Where Our Prompt Data Comes From

  • Real prompts people typed into AI engines, from licensed, representative consumer panels.
  • What people browsed and bought, so the questions follow real buying behaviour.
  • Large-scale search volume, used to weight each topic by how often it's asked.
  • The questions your own customers already ask, from Search Console and site search.
  • Hero products, launches and key rivals, covered whatever their search volume.

Tap a topic for details.

Brandlight turns AI visibility into action

A visibility score chart at 54.24%, rising over six weeks, on a blurred green backdrop.

You shouldn't just get another layer of data

Stop digging through 40 pages of data. Get a dedicated AI strategist who tells you what the numbers mean and what to do next.

Before: a table titled “40 pages of data”, with columns for query, engine, category, most cited source, your mentions, competitor mentions and sentiment, paginated to page 40.After: “Clear takeaway. Prioritized actions.” A key takeaway on where visibility is lost, and the top three actions — improve coverage on comparison keywords, strengthen presence on key third-party sources, refresh pricing and value messaging — reviewed today by an AI strategist.
  • One question, “What does Arden Night Cream cost?”, answered three ways: $380 on the brand’s own site (accurate), $295 on a retailer listing (outdated) and $240 on Wikipedia (wrong) — AI quotes $295 in 6 of 10 responses.Brand Entity

    Catch the facts AI gets wrong about your brands

    Wrong prices or policy. Wrong parent company or claims that you never made. Found where customers actually see them, traced to the source, and fixed with you.

  • Visibility by location for Estée Lauder across 1,131 location results: sub-brands Jo Malone London, Clinique and Tom Ford, a world map shaded by visibility, and countries led by the United States at 45.85%.HQ

    One global view as more regional teams come online

    Each brand, market and language runs its own instance. HQ rolls them up, so enterprise and local work together instead of pulling in different directions.

The scoreboard is the first part.
Here's what to do about it.

What marketing leaders love about Brandlight

You.com

With Brandlight, we gain full clarity into our AI visibility - transforming insights into measurable growth, smarter positioning, and stronger customer reach.

Kady SrinivasanCMO
Kady Srinivasan, smiling, in a pale pink blouse against a rust background.
The Hartford

The Brandlight platform has been essential in providing the visibility we needed and we're highly impressed with the ongoing development of new capabilities and modules within the platform.

Garrett TubbsDirector, Digital Marketing
Garrett Tubbs, bearded, in a navy blazer and white shirt against a rust background.
Mediaocean

With Brandlight, we can finally measure and improve our AI-driven visibility - turning discovery into revenue, competitive edge, and expansion.

Aaron GoldmanCMO, Mediaocean
Aaron Goldman, smiling, in a plaid shirt against a rust background.

Win AI Visibility together

Join the world’s leading enterprises working with Brandlight. Get an actionable platform, proven playbooks, and a dedicated AEO team working with you to turn insights into measurable results.

Loved by the teams using Brandlight

G2, five stars4.9/5 · 240 reviews

Frequently Asked Questions

How is the question set built, and how do you know it represents our customers?

We build it, you don't. It comes from five sources: hundreds of millions of real prompts observed through licensed consumer panels, clickstream and purchase data, search demand, your own Search Console and site search, and your business priorities. Weighted to actual demand, labelled seven ways, audited quarterly.

Which engines and markets are live today, and what isn't?

Twelve engines: ChatGPT, Google AI Overviews, AI Mode, Gemini, Perplexity, Claude, Copilot, Grok, DeepSeek, Qwen, Mistral and Naver. Ten markets natively, in local language. Mainland China is the gap. We run Qwen and DeepSeek there, not the full domestic set, and we'd rather name that than claim it.

How is this different from the tool we already have?

The scoreboard is table stakes and you'll get one. Three things differ underneath it: we build and own the question set, coverage isn't capped or priced per prompt, and every movement decomposes into the sources behind it.

How do you control LLM variability, and how do you tell a real movement from normal volatility?

The unit is the intent cluster, never the single prompt. One prompt result is one observation and we don't read it on its own. Variability gets captured by running many permutations of each intent, a fixed core panel keeps trends comparable, and changes only surface after significance thresholds.

How do different engines compare, and why don't you give one blended number?

We give both. One weighted score you can take to the board, and the per-engine split underneath it, because the engines cite largely different sources. A blended number on its own hides the thing you need to act on, which is which surface you're actually losing.

What happens to historical trends when a model changes, or when the prompt set changes?

Every run is stored with its engine, model identifier, run ID and timestamp, and the prompt universe itself is versioned. A fixed core panel carries the comparable trend and only the quarterly audit may change it. Any realignment of old and new data gets agreed with you first.

How is sentiment measured, and what do you not claim?

Every mention is classified positive, neutral or negative, in the context of the attribute being discussed. We don't count prestige language as praise: "well-established" or "premium" stay neutral unless the context is genuinely positive. And we make no accuracy claim. Check the sources, not the score.

Who owns the data, and is it used to train models?

You own your first-party data, your prompt libraries and every output we deliver. We own the platform and the anonymised benchmarks. Your data is never used to train third-party models. At contract end you export in CSV or JSON and we delete within thirty days.

What does onboarding actually require from us?

A Search Console export, your competitor list and your brand facts. We build the prompt universe, the entity map and the dashboards from there, and a named strategist runs it with you. Most of the work is ours, which is rather the point.

Ready to Compete in the AI Economy?

Brandlight

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What can you expect from the strategy session?

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