We build the content AI answers are made of
Annapurna Influence is an Answer Engine Optimization (AEO) company, founded in 2026 and based in Texas. We produce brand content and distribute it across the sources AI answer engines actually read, so those engines cite you, describe you correctly, and recommend you when your buyers ask.
Content production and distribution is our business. Our AI visibility tracker is the add-on that comes with it, monitoring how up to seven chatbots describe you so you can see what the content is doing. The tracker measures. The content moves the number.
Plans start at $499 a month, run month to month, and every article we produce stays yours.
Why we exist
A buyer used to open Google, scan ten blue links, and pick one. Now they open ChatGPT and ask which product to buy. They get one answer, maybe three options, and a reason for each. Then they act on it.
That answer is assembled from whatever the model's retrieval layer can find about you on the open web. If it finds nothing, you are not in the answer. If it finds something stale or confused, you are in the answer as the wrong thing. Neither failure shows up anywhere you would look for it. There is no impression count, no bounce rate, no lost-deal report. The buyer just never learns you exist.
We started Annapurna Influence because that gap is invisible to the people it costs the most, and because it is fixable.
What we actually do
Prompt and keyword research. Our researchers work out the questions your buyers type into AI assistants, then rank them by buying intent and by how reachable they realistically are. Questions first, keywords second.
Content production. Our writers produce long-form articles built around a canonical answer near the top, with structured data (SoftwareApplication, FAQPage, HowTo) and explicit disambiguation from the adjacent products you keep getting confused with.
Distribution across a publisher network. Every piece ships through publisher partners and social channels whose content the retrieval layers already index. Publishing on your own blog and waiting is not a distribution strategy, and it never was.
Visibility tracking, included. We monitor how each engine describes you on your target prompts, then use those readings to decide what to refresh next.
We deliberately keep each project scoped to a handful of prompts. Tight scope makes the writing sharper and the measurement honest. A program smeared across fifty prompts produces fifty forgettable articles and no clean signal about which one moved anything.
Humans do the parts that matter
Most of this category is racing to automate content production end to end. We went the other way on the two steps where judgment decides the outcome.
Humans choose the prompts and keywords. Knowing which question a buyer actually types, and which of those questions you have a real chance of winning, takes someone who understands your category. A model can generate a hundred plausible prompts. It cannot tell you which five are worth a quarter of work.
Humans write the content. Every article goes through our writers and through review rounds with you before it ships. This is not a page generator with a subscription attached.
Automation does the work automation is good at: monitoring across engines, scoring, reporting. Those need volume and consistency. The research and the writing need someone who has read your positioning and understood it.
Grounded in published research
Our methods are built on peer-reviewed work, primarily GEO: Generative Engine Optimization (Aggarwal, Murahari, Rajpurohit, Kalyan, Narasimhan, and Deshpande), presented at KDD '24, the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. It remains the foundational study of how content earns visibility inside generative engines.
Four of its findings shape how we work:
Optimization works, and the size of the effect is measurable. The paper's methods raised source visibility by as much as 40% in generative engine responses, with gains up to 37% confirmed against Perplexity, a live commercial engine.
Credibility signals outperform everything else. Adding citations, quotations from credible sources, and concrete statistics produced the largest visibility gains of any technique tested. This is why our articles are built the way they are.
Classic SEO tactics do not transfer. Keyword stuffing, the oldest move in the book, delivered close to nothing against the study's benchmark and scored below the unoptimized baseline on Perplexity. Answer engines read for meaning, so keyword density is not the lever.
Smaller sites gain the most. When every source was optimized, lower-ranked pages benefited far more than dominant ones. In one measurement, a site ranked fifth gained over 100% visibility while the top-ranked site lost ground. Backlink authority is much weaker currency here than it is in search.
The study also found that effectiveness varies significantly by domain, and recommends targeted, domain-specific optimization. That finding is a large part of why we keep researchers and writers in the loop instead of running one template across every client.
What we believe
A mention is not a win. If ChatGPT names your company but describes the wrong product, or points the buyer at a competitor's comparison page, that response failed. We score citation rate, correct-description rate, and whether the answer gives the buyer a real next step.
Authority is not the entry fee. The research shows lower-ranked sites gaining the most from optimization, and our own testing matches it. An established domain helps. It is not a prerequisite.
This is not SEO with a new hat on. Traditional SEO optimizes for position in a list. AEO optimizes for the sentence the engine generates. Different retrieval mechanics, different content shape, different definition of success.
What we won't promise
Instant results. Indexes propagate on their own schedule. Expect one to six months before engines stabilize on new content. Anyone quoting you two weeks is selling a cache refresh, not a durable change.
A number we control. Nobody owns these ranking behaviors, and they shift month to month. What we control is the quality and the reach of the material those engines retrieve. That is the real lever, we pull it hard, and we show you every reading.
That you're stuck with us. Month to month, cancel anytime, and you keep everything we produced.
Your visibility tracker
Every plan includes monitoring, which is how you see the content working rather than taking our word for it. Depending on your tier we track ChatGPT, Gemini, Perplexity, Claude, Grok, Kimi, and DeepSeek, up to seven engines in total, across as many as 100 prompts.
We report on how each engine describes your brand, not just whether it names you. Reporting runs monthly, biweekly, or weekly depending on your plan.
The name
Annapurna is a Himalayan massif, one of the fourteen peaks above eight thousand meters. It is not the tallest mountain in the world, and it is one of the hardest to climb. Getting up it is a matter of preparation, route selection, and patience with conditions you do not control.
That is roughly the shape of AEO work, which is why the name stuck.
Who we are
We are a small team in Texas working on one problem, with researchers and writers doing the work that decides whether your content earns a citation. We publish our thinking openly on our blog, including how our scoring system works and how we select prompts for tracking. If you want to judge our methods before you talk to us, start there.
See where you stand
We will run a free AI visibility report on your brand. Ten real prompts across ChatGPT, Claude, Gemini, and Perplexity, scored and sent back in about five minutes. No call required.
Get your free AI visibility report →
Prefer to talk to a person? Reach us at [[email protected]] or through our contact page.
References
Aggarwal, P., Murahari, V., Rajpurohit, T., Kalyan, A., Narasimhan, K., & Deshpande, A. (2024). GEO: Generative Engine Optimization. Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '24), Barcelona, Spain. https://doi.org/10.1145/3637528.3671900 | https://arxiv.org/abs/2311.09735