Introducing Sonar: A New Way to Understand How AI Interprets Your Brand

Most teams think about AI visibility in terms of one question:

"Do we show up in the answer box or not?"

It’s an important question. But it’s not the whole story.

Visibility only tells you that the model included you. It does not tell you how it described you, why it chose that framing, or which signals shaped the narrative.

Sonar exposes this missing layer. It shows how answer engines actually interpret your brand and which pieces of the web are influencing that interpretation.

When you understand the “why” behind the output, you finally have agency over the narrative.

Why visibility alone isn’t enough

Visibility is a single data point. Narrative is a full system.

You can appear in an AI answer and still face three major problems.

1. The model can describe you inaccurately

If the model relies on outdated reviews, old landing pages, or shallow summaries, it can frame you around traits that no longer match your product.

You show up, but the story works against you.

2. The model can group you with the wrong competitors

This happens when third-party content places you in a category you no longer operate in or compares you to tools you are not actually competing with. Wrong grouping means wrong positioning, even if visibility is high.

3. Weak sentiment can make you sound forgettable

A neutral or vague description is just as costly as a negative one. Buyers compare emotional clarity. If the model highlights another brand’s strengths and glosses over yours, you lose that evaluation before the user ever reaches your site.

This is why visibility without context is risky.

You might appear in the answer, but the narrative could be quietly pulling you off course.

Until now, teams had no structured way to see the sentiment and reasoning behind the model’s interpretation.

Sonar changes that.

What Sonar actually does

Sonar reveals the anatomy of AI-driven sentiment. It does not guess. It does not infer. It traces the model’s interpretation back to its source so you can understand both the narrative and the pathway that created it.

Here is how it works.

1. Sonar identifies the sources shaping the model’s view

AI answers draw from a wider set of signals than most teams realize. Sonar maps the exact sources the models appear to lean on across:

• Reviews
• Forum threads
• Comparison articles
• Niche industry blogs
• Long-tail content that rarely shows up in SEO tools
• Competitor pages that mention you
• Aggregators like G2 or Yelp that contain small but emotionally meaningful snippets

These sources create the raw material that the model pieces together when forming its judgment. Sonar shows you the full landscape so you can see the real-world context behind your narrative.

2. Sonar groups every brand mention into themes that matter

Raw sentiment can be noisy. Sonar organizes every mention into practical themes that match how marketers and product teams already think about customer perception.

Common themes include:

• Pricing
• Onboarding
• Support
• Ease of use
• Reliability
• Setup friction
• Integrations
• Category-specific concerns

This makes it easy to see which parts of your story are strong, which are weak, and which are inconsistent. You are not looking at a flat positivity score. You are looking at a structured representation of what the model believes your strengths and weaknesses are.

3. Sonar extracts the exact snippet driving each sentiment

This is where Sonar becomes uniquely valuable.

For every brand mention, Sonar pulls the exact sentence or paragraph that influenced the model’s sentiment. You can click and see the original wording inside the original source.

• There are no vague trend charts.
• No abstract mood indicators.
• No generic summary text.
• You see the exact input the model processed.
• You see the tone the model picked up.
• You see exactly why the narrative formed the way it did.

This level of granularity gives you the power to fix a negative perception or amplify a positive one with precision.

You finally have a direct link between real-world content and AI interpretation.

Why sentiment matters in AEO

AEO is not about ranking pages.

It is about shaping the signals that answer engines assemble into a narrative.

When an AI model answers a buyer’s question, it does not pick a single source and summarize it. It picks patterns. It identifies common descriptions. It looks for repeated strengths, complaints, comparisons, and associations.

Sentiment drives which patterns repeat.

If the dominant narrative across the web says your product is easy to implement, the model will echo that. If the dominant narrative says your pricing is confusing or your reliability is questionable, the model will echo that too.

Sentiment influences:

• How the model positions you
• Which strengths it highlights
• Which concerns it warns buyers about
• Which categories it places you in
• Which alternative vendors it lists next to you

In other words, sentiment shapes the version of your brand the buyer sees before they ever arrive at your site. That makes sentiment a core component of your visibility, not an optional add-on. Sonar is the first tool built to measure that layer accurately.

What you can do with Sonar

Sonar gives you a new level of control over how models represent your brand. Here are the three most impactful ways teams use it.

1. Fix negative patterns before they solidify

A single outdated review can anchor a model’s interpretation for months. If Sonar surfaces a negative snippet, you can track down the source, correct the information, update the context, or replace it with something more accurate.

You can fix misconceptions before they become entrenched.

2. Amplify the strengths the model already sees

If Sonar reveals consistent praise around onboarding, support, or reliability, you can reinforce those strengths through targeted content or partnerships.

You build on the patterns the model already trusts, which increases your likelihood of being highlighted for those strengths in more answers.

3. Steer neutral mentions into a positive direction

Neutral sentiment appears more often than people expect. Sonar helps you turn neutral visibility into strategic visibility by showing you where you can add clarity, detail, or differentiation to round out the narrative.

You can take a passive mention and turn it into an advantage.

Who Sonar is built for

Sonar is designed for anyone responsible for how a brand is understood inside AI models.

• Marketing leaders who need accurate market perception
• Growth teams who track AI-driven discovery
• Founders who need to understand the narrative surrounding their category
• Enterprise teams operating in highly competitive segments
• AEO teams moving beyond visibility and into narrative control

If AI answers influence evaluation in your category, Sonar gives you the clearest window available into how your brand is being interpreted.

Key takeaway: Sonar sets a new standard for AI visibility

Sonar is the first system built to show how answer engines interpret your brand, the signals they trust, and the exact pieces shaping your narrative. It turns scattered reviews, posts, and pages into a structured map of what the model believes about you.

You get a clear view of what is helping your story, what is hurting it, and what you can influence next.

Visibility tells you whether you show up.

Sonar tells you why.

That clarity is what gives you real control in an AI-driven market.

You can try Sonar for free today.