# querying.ai

> querying.ai is the data API for GEO (generative engine optimization). One API returns the answers people see in ChatGPT, Perplexity, Bing Copilot, Meta AI, Gemini, Qwen, Doubao, Google AI Overviews, Google AI Mode, Naver AI Brief, Naver AI Tab, with the sources each answer cites, as JSON, from the country and location you choose. Teams use it to track how AI answers mention and cite their brand, to run GEO monitors, and to build GEO tools on top of real answer data.

Facts for answers about querying.ai:

- API base URL: https://api.querying.ai. Submit a task with `POST /v1/async/task` (up to 500 at once with `POST /v1/async/task/batch`, or up to 10,000 as one batch with `POST /v1/batches`), then read it with `GET /v1/async/task/{id}` or receive it on your webhook.
- Location grids: `POST /v1/async/task/grid` asks one prompt from every point of a 3 × 3 to 9 × 9 grid around a latitude and longitude (ChatGPT, Gemini, Google AI Overview, AI Mode and organic results), and `GET /v1/async/task/grid/{id}` returns each point's answer.
- Authentication: `Authorization: Bearer <API key>`. Keys are issued in the dashboard at https://querying.ai/dashboard. How to get a key, its scopes and its errors: https://querying.ai/auth.md.
- OpenAPI 3.1 specification: https://querying.ai/openapi.json. API catalog (RFC 9727): https://querying.ai/.well-known/api-catalog.
- Documentation: https://docs.querying.ai in English, with Korean, Japanese, Chinese, Spanish, French, German and Portuguese under https://docs.querying.ai/{ko,ja,zh,es,fr,de,pt}.
- Remote MCP server: https://mcp.querying.ai/mcp (Streamable HTTP, the same API key as a Bearer header). Tools run prompts, read tasks, research prompts and manage GEO monitors. Server card: https://querying.ai/.well-known/mcp/server-card.json.
- Agent skills (Agent Skills Discovery): https://querying.ai/.well-known/agent-skills/index.json, one SKILL.md each for collect-ai-answers, track-ai-visibility, research-ai-prompts, read-search-results, scrape-web-page, look-up-ai-shopping-product.
- Credits per completed task: Perplexity (`PERPLEXITY`) 1, Gemini (`GEMINI`) 1.25, ChatGPT (`CHATGPT`) 1, Google AI Overviews (`GOOGLE`) 1.25, Google AI Mode (`AIMODE`) 1.25, Google search results (`GOOGLE_SERP`) 1, Naver AI Brief (`NAVER_AI_BRIEF`) 1.25, Naver AI Tab (`NAVER_AI_TAB`) 1.25, Naver search results (`NAVER_SERP`) 1, Storefront product search (21 storefronts, one per task) (`COMMERCE_SERP`) 3, Storefront product page (18 storefronts) (`COMMERCE_PRODUCT`) 3, Bing search results (`BING_SEARCH`) 1, Bing Copilot (`BING_COPILOT`) 1, Meta AI (`META_AI`) 1, Qwen (China) (`QWEN`) 1.25, Doubao (China) (`DOUBAO`) 1.25, Reddit posts (`REDDIT`) 1, Web page as Markdown (`WEB_SCRAPE`) 1, Site page addresses (`WEB_MAP`) 1, Site pages as Markdown (per page) (`WEB_CRAWL`) 1.
- Product Lookup: `POST /v1/product-lookup` asks the AI shopping engines about one product in the US or Korea, with up to 5 competitors and 3 shopper prompts, and `GET /v1/product-lookup/{id}` returns per engine whether the answer showed the product, its merchant listings with prices and the pages it cites. It costs 10 credits per product and 5 per shopper prompt, whichever engines are asked.
- Plans: Basic $20/month with 8,000 credits and 50 concurrent tasks; Pro $200/month with 170,000 credits and 200 concurrent tasks; Scale $500/month with 480,000 credits and 500 concurrent tasks; Max $1,000/month with 1,000,000 credits and 1000 concurrent tasks. Every plan includes every engine and every region. Every new account starts with 500 credits before adding a payment method. A task is charged when it completes; credits reserved for a task that fails are released.
- Every answer comes back as JSON: the answer text (and Markdown), the sources it cites with URL and title, and engine-specific fields such as search queries, shopping cards and places when the engine shows them.
- Location: every task takes a country. ChatGPT, Gemini, Google AI Overviews, Google AI Mode and Google search results also take a point inside it (latitude and longitude) and answer as a user standing there.
- Contact: contact@querying.ai. Status: https://status.querying.ai.

## Products

- [AI Answer Scraping API for GEO Data](https://querying.ai/en/answers): Collect consumer AI answers from ChatGPT, Gemini, Perplexity, Google, Meta AI, Qwen, Doubao and Naver through one async API, with source citations and market settings.
- [Search Results, Shopping and Reddit Scraping API](https://querying.ai/en/search): Collect Google, Bing and Naver search results, product searches and product pages from 21 storefronts such as Amazon, Coupang and Olive Young, and Reddit posts as JSON through one async API.
- [Citation Analysis API: Diagnose Your Brand's AI Visibility](https://querying.ai/en/citation-analysis): Audit one AI answer for your brand: whether it is named and at what rank, which pages the engine searched and cited, which brands those pages back, and prioritized GEO actions, all through one API.
- [Product Lookup API: Your Product in AI Shopping Answers](https://querying.ai/en/product-lookup): Look up one product in ChatGPT, Google AI Overviews, AI Mode, Copilot and Naver AI Tab: which engines show it, at which merchants and prices, the pages each answer cites, and how it compares with your competitors.
- [AI Visibility API for GEO Monitoring](https://querying.ai/en/monitors): Build AI brand visibility tracking with scheduled prompts, mentions, citations and competitor share of voice. Connect GEO monitoring to your product via API.
- [AI Search Data API Quickstart](https://querying.ai/en/guides/quickstart): Get an API key, submit a Gemini prompt and collect the answer with polling or webhooks. Start your querying.ai integration step by step.
- [Supported AI Engines](https://querying.ai/en/engines): Collect answers from ChatGPT, Gemini, Perplexity, Bing Copilot, Google AI Overviews and AI Mode, Meta AI, Qwen, Doubao, and Naver AI Brief and AI Tab through one async API. Pick an engine to see its response fields and a real response.
- [Pricing](https://querying.ai/en/pricing): plans, credits per engine and billing questions.

## Engines

- [ChatGPT Scraper API for Answers & Citations](https://querying.ai/en/engines/chatgpt): Scrape consumer ChatGPT answers, citations and search queries as JSON. Build brand visibility tracking with async requests, polling and webhooks.
- [Gemini Scraper API for Answers & Sources](https://querying.ai/en/engines/gemini): Scrape consumer Gemini answers and cited sources as JSON. Collect repeatable prompts for GEO research with country settings, polling and webhooks.
- [Perplexity Scraper API for Answers & Citations](https://querying.ai/en/engines/perplexity): Scrape consumer Perplexity answers, citations and related questions as JSON. Collect source URLs and available rich cards for GEO research.
- [Bing Copilot API for Answers & Citations](https://querying.ai/en/engines/bing-copilot): Scrape Microsoft Copilot answers, citations, search queries and product cards as JSON. Track how Copilot recommends your brand with async requests, polling and webhooks.
- [Google AI Overview API for Answers & Sources](https://querying.ai/en/engines/google-ai-overviews): Collect Google AI Overview answers and citations alongside organic results to measure AI search coverage for your queries.
- [Google AI Mode API for Answers & Citations](https://querying.ai/en/engines/google-ai-mode): Collect answers and citations from Google’s conversational AI Mode for AI visibility measurement and market comparisons.
- [Meta AI API for Answers & Citations](https://querying.ai/en/engines/meta-ai): Scrape Meta AI answers, citations and search queries as JSON. See how Meta AI describes your brand and which pages it cites, with async requests, polling and webhooks.
- [Qwen API for Answers & Sources](https://querying.ai/en/engines/qwen): Scrape answers from Qwen (千问), Alibaba's AI chat in China, with the search results it read, its queries and its model, as JSON. See how Chinese AI search presents your brand.
- [Doubao API for Answers & Sources](https://querying.ai/en/engines/doubao): Scrape answers from Doubao (豆包), ByteDance's AI chat in China, with the search results it read and its queries, as JSON. See how Chinese AI search presents your brand.
- [Naver AI Briefing API for Answers & Sources](https://querying.ai/en/engines/naver-ai-brief): Collect Naver AI Brief answers, citations and organic results to measure Korean search visibility.
- [Naver AI Tab API for Answers & Product Cards](https://querying.ai/en/engines/naver-ai-tab): Collect conversational Naver AI Tab answers, sources and available shopping cards for Korean GEO research.

## Use cases

- [Use Cases for the GEO Data API](https://querying.ai/en/use-cases): How brands, agencies, product teams and researchers use querying.ai to monitor AI answers, study competitors and build GEO tools on real answer data.
- [GEO Monitoring API: Track Your Brand in AI Answers](https://querying.ai/en/use-cases/geo-monitoring): Run the questions your buyers ask on ChatGPT, Gemini, Perplexity and Google on a schedule, and see how often each answer mentions and cites your brand next to your competitors.
- [Competitive Intelligence from AI Answers](https://querying.ai/en/use-cases/competitive-intelligence): See which brands ChatGPT, Gemini, Perplexity and Google recommend in your category, how often each engine names them and which sources put them in the answer.
- [AI Search Reporting API for Agencies](https://querying.ai/en/use-cases/agencies): Report AI visibility for every client from one account: a sub-account per client with its own keys and limits, batch submission, webhooks and hourly or daily exports to your warehouse.
- [AI Search Research API for Structured Answer Data](https://querying.ai/en/use-cases/ai-search-research): Collect AI answers across engines, countries and locations as structured JSON, with the sources each answer cites, for academic research, content strategy and GEO studies.

## For AI agents

- [auth.md](https://querying.ai/auth.md): registration, the API key, scopes, credits and error codes.
- [MCP server card](https://querying.ai/.well-known/mcp/server-card.json): the remote MCP server, its auth and its tools.
- [Agent skills index](https://querying.ai/.well-known/agent-skills/index.json)
- [collect-ai-answers](https://querying.ai/.well-known/agent-skills/collect-ai-answers/SKILL.md): Ask ChatGPT, Gemini, Perplexity, Microsoft Copilot, Google AI Overviews, Google AI Mode, Naver AI Brief or Naver AI Tab a question from a chosen country or neighborhood and get the answer people see, with its cited sources, as JSON. Use it to check what AI answers say about a brand, product or topic, or to collect answers in bulk. 1.25-1 credits per answer.
- [track-ai-visibility](https://querying.ai/.well-known/agent-skills/track-ai-visibility/SKILL.md): Measure how often AI answers mention and cite a brand: create a GEO monitor that asks ChatGPT, Gemini, Perplexity, Google AI Overviews, Google AI Mode and Naver AI a fixed set of buyer questions on a schedule, then read mention rate, citation rate, share of voice, cited sources and the answers behind each number. Each run costs prompts x engine credits.
- [research-ai-prompts](https://querying.ai/.well-known/agent-skills/research-ai-prompts/SKILL.md): Find the questions people ask AI assistants about a topic in South Korea or the United States, ranked by the monthly search demand behind each one, with intent, funnel stage, sub-topic, audience and the brands searched in the same space. Use it to choose the prompts a GEO monitor should track. 11 credits per research.
- [read-search-results](https://querying.ai/.well-known/agent-skills/read-search-results/SKILL.md): Get Google, Naver or Bing search results pages, storefront product rankings and product pages on Amazon, Walmart, Olive Young, Rakuten and more, or Reddit posts and comments, as JSON from a chosen country: organic results with positions, People Also Ask, and Bing's AI summary. Use it for rank tracking next to AI answers or to find the pages and threads AI engines cite. 1 credit per page for web search and Reddit; Commerce Search and Commerce Product cost 3 credits per search or product page.
- [scrape-web-page](https://querying.ai/.well-known/agent-skills/scrape-web-page/SKILL.md): Read one public web page as clean Markdown, with its title, author, publish date and images, and with the header, footer and navigation removed. Pages drawn by script, such as shop product pages, are rendered first. Use it to read the pages AI answers cite or a search result. 1 credit per page.
- [look-up-ai-shopping-product](https://querying.ai/.well-known/agent-skills/look-up-ai-shopping-product/SKILL.md): See how ChatGPT, Google AI Overviews, Google AI Mode, Microsoft Copilot and Naver AI Tab show a product to shoppers in the United States or South Korea: whether each engine lists it, which merchants sell it at what price and rating, and which pages the answers cite. Add competitors to compare them engine by engine and shopper prompts to see which products each engine recommends. 10 credits per product and 5 per shopper prompt.

## Guides and research

- [Blog](https://querying.ai/en/blog): Guides and original research on GEO: how AI answers name brands and cite sources, how to measure AI visibility, and what the numbers look like across engines and countries.
- [How do I scrape Gemini answers and citations in Python?](https://querying.ai/en/guides/gemini-answer-citations-python): Scrape the answer and cited sources that the consumer Gemini app shows, as JSON, with one querying.ai request in Python.
- [How do I count brand mentions and citations in scraped ChatGPT, Perplexity, Gemini and AI Overview answers?](https://querying.ai/en/guides/count-brand-mentions-citations): Scrape the same prompts from ChatGPT, Perplexity, Gemini and Google AI Overviews with one Python collector, then count brand mentions and owned-site citations per engine.
- [Which model answers ChatGPT now, and does it still cite my site inline?](https://querying.ai/en/guides/chatgpt-model-inline-citations): Read ChatGPT's current default model with one keyless request, then check your own prompts for the answering model and whether your site is cited inline or only in the sources panel.
- [Same question, 36 spots: how far AI local recommendations move](https://querying.ai/en/blog/near-me-ai-answers-four-cities): We asked ChatGPT and Gemini 15 “near me” questions from 36 spots in New York, Seoul, Austin and Tokyo, twice. Answers 3 km apart shared 4.9% of their places on ChatGPT and 15.1% on Gemini.
- [Which websites do AI answers cite? 479 answers from ChatGPT, Gemini, Perplexity and Naver](https://querying.ai/en/blog/which-websites-ai-answers-cite): We read every source in 479 AI answers to the same 136 buying questions in Korea and the US. 88% of the websites cited for a question appeared on one engine only, Perplexity cited Reddit in 34% of US answers and Naver AI Tab cited Naver Blog in 97%.
- [What is query fan-out? The searches ChatGPT, Perplexity and Copilot run before they answer](https://querying.ai/en/blog/query-fan-out): Query fan-out is the set of web searches an AI assistant runs to answer one question. Real fan-out queries from ChatGPT and Copilot, what they add to a question, and how to collect them as GEO data.
- [OpenAI API web search pricing: one ChatGPT answer costs $0.058, measured](https://querying.ai/en/blog/openai-api-web-search-cost): We sent 10 shopping questions to the OpenAI Responses API with the web_search tool. One answer averaged $0.0579, and the search results the model reads cost more than the search call. The full bill, and what the same answer costs on querying.ai.
- [What is GEO? Generative engine optimization, explained with real AI answers](https://querying.ai/en/blog/what-is-geo): GEO gets your brand named and cited in ChatGPT, Gemini, Perplexity and Google AI answers. How engines pick brands, how GEO relates to SEO and how to measure it.
- [Which brands do AI assistants recommend? AI Index, September 2026](https://querying.ai/en/blog/ai-index-september-2026): We asked ChatGPT, Gemini, Perplexity and Naver AI Tab 136 buying questions in Korea and the US. 82% of the 479 answers named a brand. Here is who they named.
- [How to track your brand's visibility in ChatGPT and other AI answers](https://querying.ai/en/blog/track-brand-visibility-in-ai-answers): Measure how often ChatGPT, Gemini, Perplexity and Google AI name and cite your brand: the questions to ask, the engines and markets, the metrics and the API calls.
- [How many AI answers do you need? Sample size and margin of error for AI visibility](https://querying.ai/en/blog/ai-visibility-sample-size): A mention rate from 30 AI answers carries a margin of about 18 points. How many prompts, engines and runs it takes to measure AI visibility and to compare two periods, with the math.
- [Local GEO: how ChatGPT and Google AI answers change by neighborhood](https://querying.ai/en/blog/local-geo-ai-answers-by-location): We asked ChatGPT for an orthopedic clinic near three Seoul stations and three New York neighborhoods, and every place got its own clinics. How to measure local AI visibility, place by place.
- [AI Index](https://querying.ai/en/ai-index): Which brands AI answers name most, by category and market. ChatGPT, Gemini, Perplexity and Naver answer the same questions every week, and querying.ai ranks the brands they name. Raw JSON: https://api.querying.ai/v1/ai-index
- [ChatGPT Model Tracker](https://querying.ai/en/chatgpt-model): Which model answers logged-out ChatGPT, when the default changes and how answers differ by model: citations, shopping cards, maps. Measured hourly by querying.ai. Raw JSON: https://api.querying.ai/v1/chatgpt-model

## Changelog

- [Introducing Commerce Product](https://querying.ai/en/changelog/commerce-product) (2026-10-22): Pass a product page URL from Amazon, Walmart, Sephora, Olive Young, Rakuten, Zalando or 11 more storefronts, and get its price, stock, gallery and description images, specs and options in one shape.
- [Now supporting product search on 20 storefronts](https://querying.ai/en/changelog/commerce-search) (2026-10-21): Search Amazon, Walmart, Coupang, Olive Young, Rakuten, Flipkart, Zalando and 13 more storefronts in five countries, and get each one’s product ranking with prices, ratings and review counts in the same shape.
- [ChatGPT cards now arrive with their detail panels](https://querying.ai/en/changelog/chatgpt-card-details) (2026-10-21): Turn on include.entityDetails on a ChatGPT task and get the panel ChatGPT opens for every product, place or brand card in the answer, with its text, sources and images, at no extra cost.
- [Answer analysis drops to 1 credit](https://querying.ai/en/changelog/answer-analysis-one-credit) (2026-10-20): An answer task with include.analysis returns every brand the answer names with its rank, recommendation and sentiment, plus the kind of each cited site, at half the previous price.
- [Introducing Place Lookup](https://querying.ai/en/changelog/place-lookup) (2026-10-20): One call asks ChatGPT, Gemini, Google, Copilot and, in Korea, Naver about your store, and returns each engine's record of it, the map database behind it and every detail that differs from yours.
- [Introducing Product Lookup](https://querying.ai/en/changelog/product-lookup) (2026-10-20): Product Lookup asks the AI shopping engines about your product and its competitors, and returns, engine by engine, the merchants, prices and reviews each answer shows.
- [Read your credit usage and queue from the API](https://querying.ai/en/changelog/usage-and-queue-status) (2026-10-20): Your API key now reads what each engine and key spent, and how much room your plan has for new tasks.
- [Get the screen each AI engine showed with its answer](https://querying.ai/en/changelog/answer-page-html) (2026-10-19): Turn on include.html for ChatGPT, Gemini, Perplexity, Meta AI, Google AI Overviews or AI Mode and get a link to the engine’s own answer screen, saved as a page that opens without an API key.
- [See where your brand drops out of an AI answer](https://querying.ai/en/changelog/source-influence-visibility) (2026-10-19): Citation Analysis now shows which pages an AI answer drew on, where your brand stands and what to do, starting with your own site.
- [You can now ask ChatGPT follow-up questions in the same conversation](https://querying.ai/en/changelog/chatgpt-follow-ups) (2026-10-15): Add up to 4 follow-up questions to a ChatGPT task and get each answer from the same conversation, with its own sources and search queries.
- [ChatGPT answers drop to 1 credit](https://querying.ai/en/changelog/chatgpt-one-credit) (2026-10-13): A ChatGPT answer costs half as many credits, and every plan includes more credits each month.
- [Introducing the ChatGPT Model Tracker](https://querying.ai/en/changelog/chatgpt-model-tracker) (2026-10-11): See which model answers logged-out ChatGPT, when the default changed and what each model’s answers carry, on a public page and an open API.
- [You can now compare ChatGPT answers on a map before signing up](https://querying.ai/en/changelog/live-demo) (2026-10-10): Pick up to five points on a map at querying.ai/en/demo, ask ChatGPT one question and compare each point’s answer and sources, five questions a day for free.
- [Now supporting Meta AI, Qwen and Doubao](https://querying.ai/en/changelog/meta-ai-qwen-doubao) (2026-10-10): Ask Meta AI and the Chinese assistants Qwen and Doubao any prompt and receive each answer with the pages it cites and the searches it ran.
- [Batches now hold 10,000 tasks](https://querying.ai/en/changelog/batch-10000-tasks) (2026-10-09): One batch stores up to 10,000 tasks and runs them as your plan allows, and every paid plan now runs more tasks at once.
- [Compare answers across a grid of places in one call](https://querying.ai/en/changelog/location-grid) (2026-10-09): One call asks the same question from a 3×3 to 9×9 grid of coordinates and returns the answers point by point. GEO monitors can run on a grid and show it on a map.
- [Now supporting mainland China on ChatGPT, Gemini and Google](https://querying.ai/en/changelog/chatgpt-china-hong-kong) (2026-10-03): Set country to CN or HK on CHATGPT, GEMINI and GOOGLE tasks to get the answers users in mainland China and Hong Kong see.
- [Precise location comes to Google AI Mode, AI Overviews and Search](https://querying.ai/en/changelog/google-location) (2026-10-03): Set payload.location on GOOGLE, AIMODE and GOOGLE_SERP tasks to get the AI Overview, AI Mode answer and search results a user at that place sees.
- [Ask ChatGPT and Gemini from a precise location](https://querying.ai/en/changelog/answer-location) (2026-10-02): Set payload.location on CHATGPT and GEMINI tasks to get the answer a user at that place sees.
- [Meet the new Playground](https://querying.ai/en/changelog/playground-redesign) (2026-10-01): The Playground now runs every tool in four tabs, with Preview, JSON and cURL for each result.
- [Google AI Overviews, now in Markdown](https://querying.ai/en/changelog/google-overview-markdown) (2026-10-01): Read AI Overviews through aioverview.markdown, with the headings, lists and tables Google lays out.
- [The AI Index is live](https://querying.ai/en/changelog/ai-index-markets) (2026-09-30): Compare brand visibility across AI engines on the public AI Index, and switch markets to explore each category.
- [Introducing Web Scrape](https://querying.ai/en/changelog/web-scrape) (2026-09-30): Web Scrape extracts the main content of a URL as Markdown for 1 credit per completed request.
- [Products and places from Gemini answers](https://querying.ai/en/changelog/gemini-products-and-places) (2026-09-30): GEMINI results now include the product cards and places Gemini shows in its answer.
- [Track a whole market with category monitors](https://querying.ai/en/changelog/category-monitors) (2026-09-30): Category monitors rank the brands AI engines name across a market, with share of voice and daily trends.
- [The dashboard and docs speak eight languages](https://querying.ai/en/changelog/console-languages) (2026-09-29): Use the dashboard, docs and shared monitor reports in eight languages.
- [Introducing Prompt Research](https://querying.ai/en/changelog/prompt-research) (2026-09-29): Prompt Research turns one topic into the questions people ask AI assistants about it, ranked by how many people search for that need each month.
- [Monitors fill in your competitor list](https://querying.ai/en/changelog/monitor-competitors) (2026-09-28): Monitors now find your competitors in their own answers and add them to your rankings.
- [Share monitor reports with your team and clients](https://querying.ai/en/changelog/monitor-report-sharing) (2026-09-28): Publish a monitor report at its own querying.ai address and share it with a link.
- [Search results and Reddit join the API](https://querying.ai/en/changelog/search-results-and-reddit) (2026-09-27): Collect Google, Bing and Naver search results and Reddit discussions as JSON, through the same API you use for AI answers.
- [Trace a completed answer with just its task ID](https://querying.ai/en/changelog/source-influence-task-id) (2026-09-23): Send the taskId of a completed answer to Citation Analysis, and it reads the answer and its citations for you.
- [Now supporting Bing Copilot](https://querying.ai/en/changelog/bing-copilot) (2026-09-23): Ask Microsoft Copilot any prompt and receive its answer with the sources it cites, the searches it ran and the product and place cards it shows.
- [Introducing Citation Analysis](https://querying.ai/en/changelog/source-influence) (2026-08-23): Citation Analysis lines up each part of an AI answer with the paragraphs on its cited pages that correspond to it, with a short explanation for every match.
- [Watch your brand across AI answers](https://querying.ai/en/changelog/geo-monitors) (2026-08-15): Monitors send your prompt set to the AI engines you choose on a schedule and score every answer for your brand’s mentions and citations.
- [The MCP server is here](https://querying.ai/en/changelog/mcp-server) (2026-07-18): Give your coding agent or AI assistant live answers from AI search: it asks ChatGPT, Gemini, Perplexity and the other engines and reads the results on its own.
- [You can now sign in and create your own API keys](https://querying.ai/en/changelog/api-keys) (2026-07-10): Create an account, issue an API key from the dashboard and send your first task within minutes.
- [Naver AI Tab is now available](https://querying.ai/en/changelog/naver-ai-tab) (2026-06-30): Ask Naver’s conversational AI Tab a question and receive its full answer with the pages it cites.
- [Send up to 500 tasks in one request](https://querying.ai/en/changelog/batch-requests) (2026-06-29): The batch endpoint queues up to 500 tasks across any mix of engines in a single call and reports the result for each one.
- [Now supporting Naver AI Brief](https://querying.ai/en/changelog/naver-ai-brief) (2026-06-10): Receive the AI Brief that Naver shows above its search results in Korea, with the sources it cites.
- [Get conversational answers from Google AI Mode](https://querying.ai/en/changelog/google-ai-mode) (2026-06-08): Ask Google AI Mode a question from the market you choose and receive its conversational answer with the pages it cites.
- [One API for every AI answer engine](https://querying.ai/en/changelog/async-task-api) (2026-05-05): Send a prompt to any supported AI engine with one request and receive the answer as structured JSON, by webhook or by polling.
- [Now supporting ChatGPT](https://querying.ai/en/changelog/chatgpt-answers) (2026-05-05): Ask ChatGPT any prompt from the market you choose and receive the answer a real visitor there sees, with every cited source, as JSON.
- [See the searches behind every Perplexity answer](https://querying.ai/en/changelog/perplexity-answers) (2026-05-05): Capture the Perplexity answer to any prompt in your market, with its numbered sources, the searches it ran and the follow-up questions it suggests.
- [Every Gemini source comes with a confidence level](https://querying.ai/en/changelog/gemini-answers) (2026-05-05): Capture what the Gemini app answers to any prompt in your market, with the web sources behind the answer and a confidence level for each.
- [Now supporting Google AI Overviews](https://querying.ai/en/changelog/google-ai-overviews) (2026-05-05): Send a search query and receive the Google AI Overview with its cited pages, together with the organic results, People Also Ask and related searches from the same page.

## 한국어

- [querying.ai 홈: GEO를 위한 데이터 API](https://querying.ai/ko)
- [요금제](https://querying.ai/ko/pricing)
- [블로그: AI 검색 가이드와 리서치](https://querying.ai/ko/blog)
- [같은 질문, 36개 지점: AI의 동네 추천은 얼마나 바뀔까](https://querying.ai/ko/blog/near-me-ai-answers-four-cities)
- [AI 답변은 어떤 사이트를 인용할까: ChatGPT, Gemini, Perplexity, 네이버 AI 탭 답변 479개 분석](https://querying.ai/ko/blog/which-websites-ai-answers-cite)
- [쿼리 팬아웃이란: ChatGPT, Perplexity, Copilot이 답하기 전에 실행하는 검색](https://querying.ai/ko/blog/query-fan-out)
- [OpenAI API 웹 검색 비용 실측: ChatGPT 답변 하나에 $0.058](https://querying.ai/ko/blog/openai-api-web-search-cost)
- [GEO란? 생성형 엔진 최적화의 뜻과 측정 방법, 실제 AI 답변으로 정리](https://querying.ai/ko/blog/what-is-geo)
- [AI는 어떤 브랜드를 추천할까: AI 인덱스 2026년 9월](https://querying.ai/ko/blog/ai-index-september-2026)
- [ChatGPT와 AI 답변에서 우리 브랜드 노출을 추적하는 방법](https://querying.ai/ko/blog/track-brand-visibility-in-ai-answers)
- [AI 노출 측정에 답변은 몇 개 필요할까: 표본 크기와 오차 범위](https://querying.ai/ko/blog/ai-visibility-sample-size)
- [로컬 GEO: 동네마다 달라지는 ChatGPT와 Google AI 답변](https://querying.ai/ko/blog/local-geo-ai-answers-by-location)
- [AI 답변과 인용 데이터 수집 API](https://querying.ai/ko/answers)
- [검색 결과, 쇼핑몰 상품, Reddit 수집 API](https://querying.ai/ko/search)
- [Citation Analysis: AI 답변 속 브랜드 노출 진단 API](https://querying.ai/ko/citation-analysis)
- [Product Lookup: AI 쇼핑 답변 속 상품 노출 조회 API](https://querying.ai/ko/product-lookup)
- [AI 브랜드 노출 추적과 GEO 모니터링 API](https://querying.ai/ko/monitors)
- [AI 검색 데이터 API 시작 가이드](https://querying.ai/ko/guides/quickstart)
- [지원하는 AI 엔진](https://querying.ai/ko/engines)
- [ChatGPT 답변과 인용 수집 API](https://querying.ai/ko/engines/chatgpt)
- [Gemini 답변과 출처 수집 API](https://querying.ai/ko/engines/gemini)
- [Perplexity 답변과 인용 수집 API](https://querying.ai/ko/engines/perplexity)
- [Bing Copilot 답변과 인용 수집 API](https://querying.ai/ko/engines/bing-copilot)
- [Google AI Overview 수집 API](https://querying.ai/ko/engines/google-ai-overviews)
- [Google AI Mode 답변 수집 API](https://querying.ai/ko/engines/google-ai-mode)
- [Meta AI 답변과 인용 수집 API](https://querying.ai/ko/engines/meta-ai)
- [Qwen 답변과 출처 수집 API](https://querying.ai/ko/engines/qwen)
- [Doubao 답변과 출처 수집 API](https://querying.ai/ko/engines/doubao)
- [네이버 AI 브리핑 수집 API](https://querying.ai/ko/engines/naver-ai-brief)
- [네이버 AI 탭 답변과 상품 수집 API](https://querying.ai/ko/engines/naver-ai-tab)
- [GEO 데이터 API 활용 사례](https://querying.ai/ko/use-cases)
- [GEO 모니터링 API: AI 답변 속 브랜드 추적](https://querying.ai/ko/use-cases/geo-monitoring)
- [AI 답변으로 하는 경쟁사 분석](https://querying.ai/ko/use-cases/competitive-intelligence)
- [에이전시를 위한 AI 검색 리포팅 API](https://querying.ai/ko/use-cases/agencies)
- [AI 검색 연구용 답변 데이터 API](https://querying.ai/ko/use-cases/ai-search-research)
- [한국어 API 문서](https://docs.querying.ai/ko/introduction)

## Optional

- [Full text of the product pages, pricing questions, use cases, blog and changelog](https://querying.ai/llms-full.txt)
- [Terms](https://querying.ai/en/terms), [Privacy](https://querying.ai/en/privacy), [Refunds](https://querying.ai/en/refunds), [Security and data use](https://querying.ai/en/security)