Get your brand recommended onChatGPT

Annapurna Influence is a marketing company built for Answer Engine Optimization (AEO). We produce structured, citation-ready content about your brand and distribute it across the publisher and social surfaces that AI answer engines already index. The result: when a buyer asks ChatGPT, Claude, Gemini, Perplexity, or Grok about your category, the engine describes and recommends your brand instead of guessing or naming a competitor. We were founded in 2026 and are based in Texas. More about us →

AEO stands for Answer Engine Optimization. It is the practice of shaping content so AI answer engines cite and describe your brand accurately inside the answer itself, rather than ranking you somewhere in a list of blue links.

Yes. Some teams call the same discipline GEO (Generative Engine Optimization). Same idea, same mechanics, different acronym.

Traditional SEO optimizes for a ranked list of links. AEO optimizes for the sentence an engine generates when a buyer asks a question. Different retrieval mechanics, a different content shape, and a different success metric: not "where do I rank" but "what does the AI say about me, and does it send the buyer to the right next step." Read: SEO vs. AEO — Two Games, One Battle for Attention →

No. AEO and SEO are complementary. Google's AI Overviews still draw on Google's index, so search fundamentals continue to matter. AEO adds the layer that traditional SEO was never designed to cover: how a generative engine describes you.

ChatGPT (Search), Google Gemini and AI Overviews, Perplexity, Claude, and Grok, with Kimi and DeepSeek added on our top tier. These engines share a retrieval-augmented architecture: they issue web lookups and condition their answers on what they find. That shared mechanic is what lets one content program move the needle across all of them at once.

Brands that get discovered through research rather than walk-in traffic: local and regional service businesses, SaaS and D2C companies, professional services, and agencies buying on behalf of clients. If your buyers ask questions before they buy, AI answer engines are already shaping those decisions.

No. In controlled tests, content published on a fresh, unauthoritative domain, with no ads, PR, or backlink building, shifted how AI engines described a product from "doesn't exist" to "recommended" inside 33 days. Existing authority helps, but it is not a prerequisite.

Yes, and the mechanics are different from search rankings in ways that can favour smaller players. Read: 11 Ways Small Businesses Compete for AI Chatbot Attention Against Brands With 100x the Data →

Billions of people now use AI assistants every month, and for a growing share of everyday questions an AI answer has replaced a page of search results. If your brand is not part of what those engines draw from, you are invisible at the exact moment a buyer is deciding. Read: How Many People Actually Use AI in 2026 → · Why every brand needs a strategy for AI visibility →

You can absolutely start in-house, and our blog is written to help you do exactly that. What is hard to replicate alone is the distribution footprint and the discipline of refreshing coverage every month while the indexes catch up. Read: Why Brands Need a Partner for AI Chatbot Visibility →

• You fill in your brand basics. Category, competitors, positioning, and the buyers you want to reach. This becomes the ground truth every prompt and article is tuned against.
• We create your project and scope it tightly so the content stays sharp and the tracking signal stays clean.
• We research your prompts and keywords — the questions your buyers actually type into AI assistants.
• We prioritize and baseline them, so every later change is measured rather than guessed.
• We create content built around a canonical answer, structured data, and explicit disambiguation from adjacent products.
• We release it to publisher partners and social channels the retrieval layers already index.
• We monitor and refresh, tracking how each engine describes you across your target prompts.

Your category and positioning, your main competitors, the buyers you are trying to reach, and a few disambiguation details: any aliases or trading names, any real companies that share your name, and the geography you actually serve. That last set is what stops a look-alike company from polluting your reporting.

We start with the business rather than with automation. We combine human research, search data (volume, difficulty, intent, geography), and AI-assisted analysis to find the intersection of search demand, customer intent, and business relevance. We would rather track a smaller, carefully researched set than hundreds of loosely related prompts that make the dashboard look busy. Read the full method →

Yes. If you already know the questions, services, products, or topics that matter to your business, those can go straight into the tracking strategy.

Three, mapped to stages of the buying journey:

• Type A — brand-aware. "Tell me about [Brand]." The buyer already knows you and is checking reputation, services, or fit.
• Type B — solution-seeking. "Plumber near me." They know what they need but not who to call. Strong commercial intent.
• Type C — problem-aware. "Why is my car making a strange noise?" They have a problem but have not yet worked out what solves it. This is the stage almost nobody tests for, and where being present earns you a place in the consideration set before a competitor is ever named.

Read: How to Write Better Prompts for Tracking Brand Visibility →

Long-form articles built around a canonical answer near the top, structured data (SoftwareApplication, FAQPage, HowTo), and explicit disambiguation from adjacent products. Volume depends on your plan: 10 releases a month on Starter, 20 on Growth, 40 on Scale.

Across publisher partner platforms and social channels that the retrieval layers already index — 3 platforms on Starter, 5 on Growth, 7 on Scale. Publishing where the engines already look is the difference between content that exists and content that gets retrieved.

Yes. The Starter plan includes one review round per piece, Growth includes two, and Scale includes three. If we do not receive feedback from you, we will proceed with publishing the content automatically.

We use AI tools as part of our production process, alongside human research and review. As our Terms of Use set out, AI-assisted content should be reviewed before publication, which is exactly what your review rounds are for. Nothing goes out describing your brand without your positioning as the ground truth behind it.

Because retrieval layers do not read an article the way a person does. They pull passages. Content broken into clear, self-contained sections with a canonical answer near the top is far easier for an engine to lift and cite accurately. Read: Why Chunking Matters →

It matters more than it used to. Experience, Expertise, Authoritativeness, and Trust once decided where you sat in a list of links. Now they help decide whether an engine mentions you at all. Read: What Is E-E-A-T and How Does It Affect Brand Visibility in AI Search? →

We track how each engine describes your brand, not just whether it mentions you. That includes citation rate on target prompts, correct-platform description rate, and actionable-next-step rate. A response that name-drops you but sends the buyer somewhere wrong is a failure, not a win.

It is the average prominence of your brand across every tracked response. Each response gets a weighted score of 100 ÷ your position in the answer, so being named first is worth 100, second is worth 50, fifth is worth 20, and not being mentioned is worth 0. The visibility score is the average of those. The formula mirrors real reading behaviour: attention drops sharply after the first two or three items in a list. Read the full scoring breakdown →

The percentage of tested prompts where an AI engine mentioned you at all. Think of it as awareness, where the visibility score is loudness.

A single quality-of-mention number per response. We add up position, accuracy, sentiment, depth, whether a source was cited, and whether there was a call to action, then multiply by how hard the question was. Brand-aware questions carry a weight of 1.00, narrowed-problem questions 1.25, and brand-unresolved problem questions 1.50 — because being volunteered as the answer when nobody asked for you by name is worth considerably more.

Every AI response is graded against nine fields: whether you were mentioned, how confident the match is, the exact quoted evidence, your position, sentiment, factual accuracy, depth, whether a source was cited, and whether there was a call to action. It is what turns a wall of chatbot text into numbers you can act on.

It will not count. Before anything gets scored, we verify that the name in the answer is actually you, cross-checking against your aliases, any known name collisions you have registered, and your real service area. If the check comes back low-confidence, we treat the row as not mentioned rather than let a false positive inflate your score. The evidence stays in the audit trail so you can see what happened.

No. If the same prompt runs several times on the same engine in a day, only the newest completed result counts toward your dashboard. Re-running gets you fresher numbers, never bigger ones

Monthly on Starter, biweekly on Growth, and weekly on Scale.

Because these systems are not deterministic. Ask the same question twice, minutes apart, and you can get a noticeably different answer. That is exactly why a single spot-check tells you nothing and why we run prompts repeatedly across engines and track the trend rather than the snapshot.

No, and you should be sceptical of anyone who does. We do not control what any AI engine outputs. What we control is the quality, structure, and distribution of the material those engines retrieve from, and we report honestly on what changes as a result.

Expect 1 to 6 months before effects stabilize. That is the propagation delay of the underlying indexes — Bing for ChatGPT, Perplexity's own retrieval layer, Google for AI Overviews, and others. After that, the effect compounds: more citations, more accurate descriptions, more buyers landing on the right next step.

Because publishing content is not the slow part. Waiting for each engine's index to crawl, ingest, and stabilize on the new material is. This is documented AEO behaviour, not lag in our workflow.

You keep the content we have produced for you and it stays published. What stops is the refresh cycle. Coverage that is not maintained tends to erode over time as engines re-index and competitors keep publishing, so the compounding works in reverse.

We ask ChatGPT, Claude, Gemini, and Perplexity 10 real-world prompts about your brand, score the answers with the same model our paying customers use, and email you the breakdown. It shows exactly where you show up and where you do not. Get your free report →

No. No credit card, and no sales call.

Yes. Our plans are managed through Stripe, and you can easily manage your subscription directly from there.

No. Your monthly price covers everything listed in your plan: research, content production, distribution, and monitoring. There is no media buy involved.

Yes — if you are managing several brands or need volume beyond Scale, contact us and we will put together a scope.

Everything we know is on the blog. Good places to start:

• How to Get Your Brand Mentioned on AI Chatbots — the plain-English introduction
• SEO vs. AEO — Two Games, One Battle for Attention — why this is a different discipline
• How the Annapurna Influence Scoring System Works — every number on your dashboard, with worked examples
• How Annapurna Selects Prompts for Tracking and Data Generation — our research method
• How to Write Better Prompts for Tracking Brand Visibility — a guide you can run yourself today

Get a free AI visibility report to see where you stand, or talk to us.