{"id":82497,"date":"2026-09-09T16:42:13","date_gmt":"2026-09-09T08:42:13","guid":{"rendered":"https:\/\/www.ahhhhfs.com\/82497\/"},"modified":"2026-09-11T21:29:18","modified_gmt":"2026-09-11T13:29:18","slug":"niubigeo","status":"publish","type":"post","link":"https:\/\/www.ahhhhfs.com\/en\/82497\/","title":{"rendered":"NiubiGEO: Open-Source, Self-Hosted AI Brand Visibility Tool"},"content":{"rendered":"

NiubiGEO is an open-source, self-hosted AI brand visibility tool.<\/strong> It uses model APIs to show how AI describes your product, which other brands appear in the response, and what citations or links are returned.<\/p>\n

\"NiubiGEO<\/picture><\/a><\/p>\n

You can begin with a domain test to see how different models understand and describe a website. After selecting relevant keywords, you can also check which products appear when the target brand is not included in the query. These two workflows answer different questions: \u201cHow does AI describe my product?\u201d and \u201cWhich products appear for this topic?\u201d<\/p>\n

The records come from the APIs and models selected for each test. Model choice and web search settings can affect the output, so the results may differ from what users see in the ChatGPT, Claude or Gemini web interfaces.<\/p>\n

What can NiubiGEO show you?<\/h2>\n

After a test is complete, NiubiGEO organizes the product descriptions, competing brands, keywords, citations and previous runs. You can review the report by asking five practical questions.<\/p>\n

\"PostHog<\/picture><\/a><\/p>\n

1. Did the AI describe your product correctly?<\/strong> Check how the model categorizes the product, whether it misses important features, and whether it claims the product provides services that it does not offer. You can also compare descriptions returned by different models.<\/p>\n

2. Which other products appeared in the response?<\/strong> Review the brands that the model places alongside your product, then decide whether they are direct competitors or only loosely related alternatives.<\/p>\n

3. Which products appear when your brand is not named?<\/strong> After choosing a keyword to test, you can see which products are mentioned, which ones receive a clear recommendation, and whether your own product appears.<\/p>\n

4. What links did the response include?<\/strong> Open the original response and check provider citations separately from ordinary URLs in the answer. These links show which pages were returned with the response, although they do not prove why the model mentioned or recommended a product.<\/p>\n

5. What changes in later tests?<\/strong> Saved records make it possible to compare product descriptions, brand mentions and citations across different runs.<\/p>\n

Does an AI mention count as a recommendation?<\/h2>\n

No. A brand name appearing in an answer only shows that it was mentioned in that particular response. To count as a recommendation, the answer should connect the product with a user requirement and explain why someone might choose it.<\/p>\n

1. A simple brand mention:<\/strong> The product appears in a list of names, but the answer does not explain who it is for or what problem it solves.<\/p>\n

2. A recommendation with a reason:<\/strong> The answer connects the product with factors such as price, team size or a particular use case, then explains why it may be worth considering.<\/p>\n

3. A related link:<\/strong> The response includes a product website, review or community page. You can open the page to inspect the information, but the presence of a link does not prove that it caused the recommendation.<\/p>\n

For this reason, an AI visibility report is more useful when you examine where the brand appeared, how the model described it and whether it supplied a clear recommendation. Counting mentions alone leaves out much of that context.<\/p>\n

Explore real NiubiGEO cases before self-hosting<\/h2>\n

The project provides 20 public domain cases<\/a>, including Notion, Figma and PostHog. You can inspect the model responses, citations and report screenshots before installing the tool or adding an API key.<\/p>\n

\"Twenty<\/picture><\/a><\/p>\n

In the Figma case, the project used \u201cPrototyping\u201d as the keyword. Some responses mainly explained the concept of prototyping, while another response mentioned Figma directly. The example shows the difference between an AI understanding a topic and naming a specific product in its answer.<\/p>\n

\"Figma<\/picture><\/a><\/p>\n

Of the 20 published cases, 10 completed the full workflow and 10 completed only part of it. Eleven included keyword measurements. Failed runs and uncertain results remain in the records, so the examples also show some of the issues that can occur during testing.<\/p>\n

How do you self-host NiubiGEO, and what does it cost?<\/h2>\n

NiubiGEO is an Apache-2.0 licensed open-source project that can run on your own computer or server. Testing a product requires your own API key and available account balance. Long-term costs may also include server resources, updates, backups and maintenance time.<\/p>\n

What do you need to deploy it?<\/h3>\n

Version 0.2.0 provides a Docker image and can also run with Node.js 22 or later. The official quick-start configuration requires an OpenRouter API key. Once configured, you can open the workbench in a browser, select a model and begin testing.<\/p>\n

Scheduled tests require a separate monitoring Worker. The project\u2019s Docker deployment guide<\/a> explains how to start it so that tests can run at the configured times and retain their records.<\/p>\n

If you already use Docker or know how to install Node.js and edit configuration files, you can follow the v0.2.0 setup instructions<\/a>. First-time self-hosting users may need additional time to prepare the environment and resolve configuration problems.<\/p>\n

What determines the API cost?<\/h3>\n