Frequently Asked Questions

Modern systems like ChatGPT, Claude, and Gemini don't rely only on what they were trained on.

They often:

• •Search for information
• •Pull relevant sources
• •Generate an answer based on what they find

This is called retrieval-augmented generation.

That means your AI “reputation” is shaped by what the models can find and trust — not just what they memorized months ago.

Yes.

You're not changing the model itself — you're changing the inputs it uses.

By improving:

• •How your company is described
• •Where that information appears
• •How structured and consistent it is

…you influence what gets retrieved and how it's interpreted.

In many cases, outputs change within days or weeks — not months.

Because updates are slow and unpredictable.

Models retrain every 6–12 months (or longer), and:

• •You don't control what data is included
• •Incorrect information can persist — or even get reinforced
• •Your buyers are using AI today, not after the next release

Waiting means leaving your first impression to chance.

No.

Most major AI systems rely on similar signals:

• •Clear entity definitions
• •Consistent information across sources
• •Structured, machine-readable content
• •Trusted domains

Instead of chasing individual models, Vantage helps you fix the underlying signal layer — so improvements show up across all of them.

SEO helps you rank pages.

PR helps you shape narratives in media.

Vantage focuses on how AI systems:

• •Interpret your company
• •Resolve conflicting information
• •Summarize you for buyers

It's not just about being visible — it's about being understood correctly.

This is one of the most damaging — and most common — AI reputation problems.

When several companies share a name, AI models often blend them together: attributing another business's leadership, location, or even controversies to you. A buyer asking about you can get a confident answer that's about someone else entirely.

Every Vantage scan reads your own website first to establish who you actually are, then checks what the models say against that ground truth. When a model is describing a different company that shares your name, we flag it as a conflation risk instead of reporting it as fact — and tell you the signals to add so the models can tell you apart.

It depends on the issue, but typically:

• •Days: new content is indexed
• •1–2 weeks: models begin retrieving improved sources
• •2–4 weeks: measurable changes in outputs

Vantage tracks this over time so you can see what's working.

Common examples include:

• •Incorrect founders or leadership
• •Confusion with similarly named companies
• •Outdated positioning or product descriptions
• •Missing or weak brand signals
• •Inconsistent descriptions across sources

Most companies have at least a few — they're just invisible until you look.

Each scan includes:

• •A breakdown of how models describe your company
• •Detected hallucinations or inconsistencies
• •Sentiment and positioning analysis
• •The sources likely influencing outputs
• •3–5 concrete actions to improve results

So you're not just seeing the problem — you can fix it.