Why VozRadar exists
Search used to be a list of links. Now buyers ask an assistant a full question and get one answer that names a few brands. Which brands get named depends on the market: people in Mexico ask different questions than people in the United States, the assistants draw on different sources, and the recommendations change.
Most tools in this space count how often a brand is mentioned. That is useful, but it leaves the important questions open. Are these the questions buyers here actually ask? Why is the competitor recommended instead of us? What should we change? Did it work?
VozRadar was built to answer all of those, in one loop: discover, measure, explain, fix, ship, prove.
What we do
Regional prompt intelligence. For a chosen market, such as Mexico in Spanish, VozRadar discovers the localized questions buyers are likely to ask an AI assistant. A market is treated as its own place, not as a translation of an English keyword list.
AI visibility measurement. Approved prompts are run repeatedly across named answer surfaces: OpenAI's models with web search through OpenAI's API (the models behind ChatGPT), Gemini with Google Search grounding through Google's API, Perplexity through its API, Claude with web search through Anthropic's API on Growth and Agency plans, and Google AI Mode and AI Overviews captured from Google's own results pages. Every answer shows the surface, market, location and time that produced it.
Source and competitor intelligence. For each market, VozRadar shows which competitors appear more often, which websites and publications are cited repeatedly, where competitors have local content you lack, and where answers contain outdated facts about your brand.
Recommendations you can ship. Findings become prioritized actions with their evidence attached, rendered as a content brief or as an implementation prompt for a coding agent. You review and ship the change; VozRadar never publishes to your site.
Experiment Ledger. Every recommendation can become an experiment with a baseline, a ship date and a follow-up observation window, so the question "did it work?" has a recorded answer.
How we measure
AI answers are not rankings. The same question, asked twice, can produce different answers, and the answer changes with the model version, the search results behind it, the location and the day. VozRadar treats every answer as one sampled observation and every metric as a rate over many observations.
That is why the product shows mention rate, recommendation rate and citation coverage instead of a position, and why every rate comes with its sample size and an uncertainty range. A recommendation rate of 31% on 40 answers is shown as exactly that.
Every surface is named precisely. An answer from OpenAI's API with web search is labelled as such, not as "ChatGPT", because an API result is not the same thing as what a consumer sees in the app. When a provider changes a model or its search behaviour, VozRadar records the change, and experiments that span it are flagged rather than silently compared.
Before-and-after results use careful language: "likely positive", "no clear change", "inconclusive". An improvement observed after a change is evidence, not proof, and the product says so.
What we do not claim
- A single generated answer is not a stable ranking.
- An API result, even with web search, is not automatically what a person sees in the ChatGPT, Gemini or Claude apps.
- Estimated AI demand is a proxy built from search and trend signals, not real prompt volume.
- A change in visibility after an intervention is an association, not guaranteed causation.
Transparency about method is part of the product. Every aggregate number links back to the answers behind it.
Where we start
VozRadar launches with Mexico and Spanish, with more Latin American markets, Brazil and selected Southeast Asian markets following. The architecture is market-neutral; the prompts, sources and benchmarks are market-specific, and a new market is only opened once it clears a published readiness bar for language, local sources and benchmark coverage.
See how AI sees your brand.
Start with one market. Expand when you're ready.