Cituna does not track DeepSeek, so start by checking it by hand: keep 10 to 20 buyer questions, ask each one on chat.deepseek.com with Search off and again with Search on, from the country you sell in, and note which brands and links each answer gives. Step 6 below has the full method.
To get cited by DeepSeek, work on the two places its answers come from: what the model already learned from the public web, and, when a user switches on Search, the web pages it looks up for that question. DeepSeek publishes no crawler name, no search partner and no brand report, so the practical work is to make your facts the same on every public page that mentions you, rank for the short searches a buyer’s question turns into, write passages that state the answer plainly, and check the results by hand with Search on and off.
What DeepSeek says about where its answers come from
DeepSeek has published less about retrieval than OpenAI, Google or Microsoft. Everything below comes from DeepSeek’s own site, policies and API documentation, read on October 9, 2026. Where it is silent, we say so.
| DeepSeek page | What it says | What it means for a brand |
|---|---|---|
| Model mechanism and training disclosure | Pre-training uses publicly available information on the internet, acquired and filtered by technical methods, plus licensed data from third-party data providers | Your brand’s public footprint at training time shapes what the model knows without searching |
| Same disclosure | Retrieval-augmented generation (RAG) is one of the techniques it uses to reduce hallucinations | Some answers are grounded in documents fetched at the time of the question |
| Home page | The chat entry offers a “Search” option next to “DeepThink” | Web lookup is a mode the user turns on, not always on |
| Terms of Use | Section 5.2 (Last Update March 27, 2026): enabling the “Search” function may improve the accuracy of the outputs to some extent | Answers with Search off rely on the model alone |
| Terms of Use, section 4.4 | Outputs may include information from third-party websites or other external sources, and DeepSeek may provide links to third-party websites in them | A cited page can appear as a link in the answer |
| Privacy Policy | Last Update February 10, 2026: DeepSeek integrates third-party APIs to provide search services and shares the user’s input keywords with them | The search provider is not named, so you cannot target one index |
| Privacy Policy | Approximate location from the IP address is used to answer questions about the user’s location, such as recommending local cuisine in their city | Local questions get local answers; test from your market |
| API reference | The chat completion reference lists no web search parameter | Apps built on DeepSeek’s API answer from the model unless they add their own search |
Sources: DeepSeek’s home page, model disclosure, Terms of Use, Privacy Policy and API reference, read October 9, 2026.
Two things DeepSeek does not publish matter as much as what it does. It names no crawler user agent for training or for search, so there is no DeepSeek token to allow or block in robots.txt. And it names no search provider, so claims that it uses one particular engine are third-party guesses, not something to plan around.
Why DeepSeek is different from the other engines
Three facts set DeepSeek apart from ChatGPT or Copilot for a brand.
- Search is opt-in. A user who leaves Search off gets an answer from the model’s training alone. That answer can only name brands that were well documented on the public web before the model was trained, which makes your long-term public record count more here than on engines that search by default.
- The model travels. DeepSeek says it releases its model weights on open-source platforms under the MIT License, and its API documentation says the API format is compatible with OpenAI and Anthropic, so the same model runs inside other people’s apps and coding tools. What it learned about you can surface in products that never show the DeepSeek name.
- New models replace the old knowledge in steps. DeepSeek’s transparency page dates DeepSeek-V3.2 to December 1, 2025 and DeepSeek-V4 to April 24, 2026, and its news page dates V4.1-Flash to September 10, 2026. A fact you publish today reaches the model’s memory only when a later model is trained on it.
How we chose these six steps
The steps follow the two paths a brand mention takes in DeepSeek: into the model through public web data, and into a Search answer through a page the search returns. Every statement about how DeepSeek works comes from DeepSeek’s own pages listed above, read on October 9, 2026; third-party studies of DeepSeek’s citation habits were not used as fact. The order is the order to do the work in, not a ranking of importance.
Step 1: Fix your public record first
Because the model learns from publicly available web data, the pages that describe you across the web, not just your own site, are your raw material. List the ten or twenty public pages that rank for your brand name: your site, review profiles, directories, comparison articles, press coverage and your own documentation. Make the basic facts agree everywhere: what you do, who it is for, your category, your prices and your headquarters. A model trained on contradictions has a reason to hedge or to name someone else. Our guide to building an entity profile for AI search lists the fields to align.
Step 2: Keep your pages readable by any crawler
DeepSeek names no crawler, so you cannot write a robots.txt rule for it. What you can control is whether your pages are open to crawlers in general. Check that a blanket disallow for unknown bots, or a firewall rule written to stop AI scrapers, is not blocking pages you want known. Put prices, product names and the direct answer in the server HTML rather than only in scripts, so any crawler that fetches the page reads them. Our guide on allowing AI crawlers in robots.txt safely covers the syntax for the crawlers that are documented.
Step 3: Rank for the searches behind your buyers’ questions
With Search on, DeepSeek sends keywords to a third-party search service and reads what comes back. It does not say which service, so the safest assumption is that the pages ranking well in the major web indexes for a short query are the ones it can read. Turn each buyer question into the few words a search would use (“crm for small law firm pricing”), check who ranks for them, and make sure you own one strong page for each. DeepSeek’s website is published in Chinese and English; if you sell in both markets, check the Chinese-language searches as well.
Step 4: Write passages that can stand on their own
DeepSeek’s terms warn that its outputs may contain errors, and its model disclosure lists retrieval as one way it reduces them. A retrieved passage helps an answer most when it states the fact without needing the rest of the page. For each question you want to be cited for:
- answer it in the first two sentences of the section that covers it;
- keep the brand, the product and the number in the same sentence;
- date anything that changes, such as prices or plan limits, so a reader and a model can tell it is current;
- give each question one owner page, so the search does not split between two of yours.
Step 5: Get named on the pages the search returns
For “best” and “which” questions, the results are mostly comparison articles, review sites and forums. Being listed there counts twice with DeepSeek: those pages can be retrieved with Search on, and they are part of the public record a future model learns from. Search your short queries, list the third-party pages that rank, and earn a place on each on its merits. Our guide to earning citations from third-party websites covers how, without paid placements.
Step 6: Check DeepSeek by hand
DeepSeek offers brands no report of how often it names them. To measure it:
- Keep a fixed list of 10 to 20 buyer questions, worded the way a buyer would type them.
- Ask each one twice on chat.deepseek.com, once with Search off and once with Search on, from the country you sell in, since DeepSeek uses your approximate location for local questions.
- Record three things each time: whether your brand is named, which rivals are named, and which links, if any, appear with the answer.
- Repeat weekly with identical wording, and again whenever DeepSeek announces a new model, because the Search-off answers can change all at once.
If you would rather not do it by hand, several trackers list DeepSeek on the dates we read their pricing pages: LLMrefs among eleven engines on its $79 plan (llmrefs.com/pricing, October 7, 2026), Rankability among eleven platforms on its $97 Starter plan (rankability.com/pricing, October 9, 2026), Rankscale among 17 or more engines on its $99 Pro plan (October 9, 2026), and Trakkr among eight listed engines, with Trakkr plans from $100 (trakkr.ai/pricing, October 1, 2026).
Cituna and DeepSeek
Cituna does not track DeepSeek. If DeepSeek is the engine your buyers use, the manual method above or one of those trackers is the way to measure it.
What Cituna does and does not cover here
Cituna does not ask DeepSeek your prompts and holds no DeepSeek data. On its paid plans it asks your buyers’ questions on ChatGPT, Perplexity, Gemini, Claude, Grok, Google AI Overviews and Google AI Mode every day, records whether each answer names you, cites you or names a rival, shows the pages each engine read, and generates the fix for each gap: schema, FAQ markup, an llms.txt entry or a new article. Search Console is joined in on every paid plan, so a gain can be tied to clicks. Cituna plans start at $39 a month for 10 prompts on one brand, and API keys work on every paid plan.
Most of the work in this guide carries over. A consistent public record, pages that rank for the short query and passages that state the answer first help with the engines Cituna tracks as much as with DeepSeek.
Drafted with AI assistance from our own research and Search Console data, and reviewed by Rahul A before publishing. Rules and prices change; check the linked official source before you act.