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Sami
Sami

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Your brand has an AI-search blind spot — and it's in China (DeepSeek, Qwen, Kimi, GLM)

TL;DR — When someone asks an AI "what's the best running-shoe brand?", that answer is the new shelf placement. There are good tools to track that on ChatGPT/Perplexity/Gemini. There are almost none for the Chinese engines — DeepSeek, Qwen, Kimi, GLM — where 900M+ people now ask instead of searching. I built one that does both in a single run. Try it on Apify.

The shelf moved into the answer

Search is being replaced by answers. People don't scroll ten blue links anymore — they ask an assistant and take the brands it names. So the question every brand now has to answer is no longer "where do I rank on Google?" but "do the AI engines even mention me — and how?"

That discipline has a name now: GEO (Generative Engine Optimization). The tooling is real and growing fast. But there's a hole in it.

The blind spot: the Chinese engines

Every GEO/AI-visibility tool I could find covers the Western engines — ChatGPT, Gemini, and friends. Almost none cover the Chinese ones: DeepSeek, Qwen/Tongyi, Kimi/Moonshot, GLM/Zhipu, where hundreds of millions of people now ask product questions, and where AI already drives a big chunk of product discovery.

If you sell into China — or your competitors do — that's the part of your AI visibility you literally cannot see today. That gap is the whole reason I built this.

What it measures

Give it your brand, the questions your customers actually ask, and the competitors you care about. For every prompt × engine it returns:

  • Mentioned? — is your brand named in the answer at all
  • Sentiment — positive / neutral / negative + a −1…1 score (English and Chinese lexicon)
  • Rank — where you sit vs the competitors you listed
  • Share of voice — you vs rivals in that specific answer
  • Cited sources — the URLs the engine surfaced (for search-enabled engines)
  • Answer snippet — the evidence behind the score

One record per brand × prompt × engine. Export JSON/CSV/Excel or pull it into your BI.

A monitor, not a one-off

A single snapshot of "does DeepSeek mention me" is nearly worthless, because AI answers are volatile — they move week to week. The value is the trend: did you just drop out of Qwen's answer? did a competitor overtake you on DeepSeek this week?

Turn on delta mode and put it on a schedule, and each run returns only what changed since last time — so a quiet week costs almost nothing and a real shift surfaces the moment it happens.

Example output

{
  "brand": "Nike",
  "engine": "deepseek",
  "prompt": "What are the best running shoe brands?",
  "mentioned": true,
  "sentiment": "positive",
  "sentimentScore": 0.5,
  "rank": 2,
  "competitorsMentioned": ["Adidas", "Li-Ning"],
  "shareOfVoice": 0.333,
  "answerSnippet": "For running shoes, the most recommended brands are Adidas, Nike and Li-Ning..."
}
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How to run it

  1. Set brand and a handful of prompts (the questions your customers ask).
  2. Pick engines and add your own API key for each in apiKeys — pure pay-as-you-go, no subscription. (Run it with no key and you get a free labeled sample so you can see the output shape first.)
  3. Add competitorBrands, turn on deltaMode, attach a Schedule → a hands-off weekly visibility feed.

Pricing is pay-per-event: $0.25 per visibility check (1 brand × 1 prompt × 1 engine), small add-ons for delta + competitors. You pay your own LLM usage on your own keys. Far below the $270–$2,000/mo enterprise GEO platforms — and the only one that sees the Chinese engines.

AI Brand Visibility Monitor on Apify

If you track brand visibility across AI search, which engines/prompts would you most want covered next (Doubao? ERNIE?)? Tell me in the comments and I'll likely ship it.

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