# geoSurge

> geoSurge is a GEO (Generative Engine Optimization) and AEO (Answer Engine Optimization) platform that helps brands and agencies become part of LLM training data, so they show up — and show up favorably — in AI-generated answers from ChatGPT, Gemini, Perplexity, Claude, and other models.

geoSurge measures how brands are represented inside large language model responses, tracks how that representation changes over time, and provides levers to influence it. Our analytical edge is working at the level of token-level model probabilities, not surface-level rankings.

## What we do

- **Track AI visibility.** Customers define the prompts they care about. We run those prompts across LLMs repeatedly, across providers, locations, and time, and report whether the brand is mentioned, in what context, and against which competitors.
- **Analyze raw LLM responses.** We surface mentions, cited sources (RAG citations), token-level probabilities, and trends.
- **Monitor LLM crawlers.** We track which AI bots — GPTBot, GeminiBot, Anthropic, Perplexity, and others — actually visit customer domains to ingest their content.

## Who we serve

- CMOs and marketing teams inside brands who need to understand and improve how they appear in AI-generated answers.
- Agencies that operate geoSurge on behalf of their clients, with multi-client workflows built in.

## Main features

- [Trends](https://app.geosurge.ai/): Brand rankings and mentions in LLM outputs over time, sliced by location and category.
- [Probabilities](https://app.geosurge.ai/): Token-level probability and perplexity explorer — geoSurge's signature feature for understanding *why* a model answered the way it did.
- [Visibility](https://app.geosurge.ai/): Continuous AI visibility tracking organized by Organization → Project → Topic, with prompts fired multiple times per day.
- [Mentions](https://app.geosurge.ai/): Brand-mention search with activity barcode charts across all tracked queries.
- [Sources](https://app.geosurge.ai/): The URLs LLMs cited via RAG / web search when constructing their answers.
- [Crawls](https://app.geosurge.ai/): Inbound LLM bot traffic tracking — which AI crawlers visited your site and what they ingested.
- Competitor tracking: Cross-cutting capability — most metrics (mentions, rankings, sources, share of voice) can be sliced against a named competitor set the customer defines.

## Key pages

- [Homepage](https://geosurge.ai/)
- [About](https://geosurge.ai/about)
- [Blog](https://geosurge.ai/posts)
- [Contact](https://geosurge.ai/contact)
- [Privacy Policy](https://geosurge.ai/privacy-policy)
- [Terms of Service](https://geosurge.ai/terms-of-service)

## Product app

- [Dashboard](https://app.geosurge.ai/) — the geoSurge application where customers configure prompts, view results, and operate campaigns.

## Vocabulary

- **AI visibility** — whether and how a brand appears inside LLM-generated answers.
- **Prompt set** — the curated list of prompts a customer wants to track per market and model. The central input to the product.
- **Raw response** — the full, unprocessed LLM answer to a tracked prompt. Everything we analyze (mentions, sources, probabilities) is derived from these.
- **Mention** — an instance of a brand name appearing inside a raw response.
- **Source** — a URL the LLM cited (typically via RAG or web search) when constructing its answer.
- **Competitor set** — the named list of competing brands a customer wants every metric sliced against.
- **Crawl** — a recorded visit by an LLM bot to a customer's site.

## Contact

- Website: https://geosurge.ai
- Contact: https://geosurge.ai/contact