AI Search Engine Deep Dive
How DeepSeek Works
The fastest-growing AI engine — and the only one that shows its reasoning
Founded
2023
HQ
Hangzhou, China
Queries/month
525M visits/mo
Growth
+130M MAU in 12 months
Architecture
Think-first RAG (DeepThink)
Cites sources
Yes, inline
Most guides about DeepSeek frame it as a Chinese competitor to ChatGPT. That framing misses what makes DeepSeek genuinely different — and why brands in French and French-adjacent markets need to start measuring DeepSeek visibility now.
DeepSeek launched its consumer chatbot on January 20, 2025. Within twelve months, it had passed 130 million monthly active users across 156 countries, hit #1 in the App Store across that footprint, and reset the cost-performance curve for frontier AI by a factor of roughly 30x. France is DeepSeek's fifth-largest country by MAU share — and its third-largest by app downloads.
Everything on this page is sourced from official DeepSeek documentation, peer-reviewed releases, and third-party crawler trackers. Where we don't have a verified source, we say so explicitly.
What is DeepSeek?
DeepSeek thinks first, searches second — exposing the full reasoning chain to the user before generating its cited answer. This is genuinely different from every other engine in this series.
Where Perplexity retrieves first and reasons over the retrieved chunks, DeepSeek inverts the flow. A feature called DeepThink shows the model's chain of thought before the answer — including the considerations it weighed, the contradictions it resolved between sources, and the search strategy it chose. The visible reasoning is not just a UX trick. It changes what gets cited, because the model documents why a source was selected.
DeepSeek-V4 Preview is live as of 2026 with stronger agent capabilities and top-tier reasoning. The model is also open-source: DeepSeek-V3 and R1 are released under permissive licenses with public weights, making DeepSeek the most-starred AI project of 2025 with over 170,000 GitHub stars across the organization.
Technical architecture
How DeepSeek retrieves and generates answers
DeepSeek's retrieval pattern is the opposite of Perplexity's. Perplexity retrieves first and reasons over the retrieved chunks. DeepSeek thinks first about how to find the best answer, then issues searches shaped by that reasoning. With DeepThink mode active, every step of this process is visible to the user — making DeepSeek the only frontier engine that exposes its full decision-making before answering.
"Transparent Thinking: When ready with an answer, DeepSeek shows its reasoning and where it is collating information by providing citations, a major shift from black-box AI models that offer little visibility into their decision-making."
BrightEdge, The Ultimate guide to DeepSeek (2025)
Query Decomposition with Visible Reasoning
When DeepThink is activated, DeepSeek begins by decomposing your query into its underlying decision structure. For a query like "best 60-inch TVs under €1000 in France," the model identifies that 60-inch is a less common size than 55 or 65, flags that some sources may conflate 58" or 65" with 60", and recognises the price-constrained European market context — all visible before any search executes.
Reasoning-Shaped Search Strategy
Rather than searching with the user's literal query, DeepSeek chooses search terms biased toward the context it has just identified — French retailers for a French query, 2025-2026 product cycles for a recency-sensitive query, technical specifications for a comparison query. The model writes down its search strategy before executing, in plain text the user can read.
Web Retrieval with Opaque Crawler Signature
DeepSeek performs web searches when needed, but its crawler footprint is poorly documented. The user-agent string DeepSeekBot has been observed in server logs, but DeepSeek itself does not publish a webmaster-facing bot policy. Web fetches during retrieval may not consistently identify themselves as bots — they sometimes appear as standard browser traffic.
Editorial note
Because robots.txt compliance cannot be verified, server-side controls (firewall, WAF, IP-range filtering) are the only enforceable option for brands wanting to block DeepSeek. Conversely, brands wanting visibility cannot rely on standard 'allow this crawler' semantics — DeepSeek visibility appears to be earned primarily through training-data presence rather than retrieval-time fetching.
Source Evaluation and Contradiction Resolution
DeepSeek's reasoning chain documents not just which sources it found, but how it weighed them against each other. When sources contradict — one claiming 60-inch TVs are rare while another lists many models — DeepThink shows the resolution logic. This favours sources that are structured, factual, and contradiction-friendly: pages that explicitly compare options, declare specifications, and resolve common confusions.
Inline Citation Generation
Citations appear in the response, often inline near the relevant claim, rather than as a separate Sources panel. The DeepThink reasoning chain also references sources during reasoning, before the final answer is formed. This means citation extraction across DeepSeek requires different tracking logic than Perplexity or ChatGPT — standard AI-visibility tools that scan for footnoted citations will under-count DeepSeek references.
Answer Delivery with Visible Reasoning
The final answer is delivered with the full DeepThink reasoning chain still visible above it. For users, this means the answer arrives with its full provenance — including which sources were authoritative and why. For brands, this means DeepThink can be used as a competitive intelligence tool: asking DeepSeek to evaluate your category and reading the visible reasoning chain reveals which sources DeepSeek considers authoritative in your space.
What we know — and what we don't
Intellectual honesty is the point of this page. Most content about DeepSeek optimization mixes verified facts with educated guesses without distinguishing between them. We don't do that.
Confirmed by official sources
- DeepThink mode exposes the model's full reasoning chain before the answer
- DeepSeek thinks first about retrieval strategy, then searches — the inverse of Perplexity's flow
- DeepSeek-V3 and R1 are open-source with public weights under permissive licences
- 130M+ monthly active users across 156 countries within 12 months of January 2025 launch
- France is the 5th-largest single-country market by MAU share, 3rd-largest by app downloads
- DeepSeek-R1 scored 97.3% on MATH-500 and DeepSeek-Coder V2 hit 85.6% on HumanEval
- DeepSeek-V3 was reportedly trained for approximately $5.5M — roughly 1/18th the cost of GPT-4
- Inline citation format differs from Perplexity's URL lists and ChatGPT's footnoted citations
Not publicly disclosed
- DeepSeek does not publish a webmaster-facing crawler policy
- Robots.txt compliance for DeepSeekBot cannot be verified
- The exact embedding model used for retrieval is undisclosed
- Whether retrieval-time fetching identifies itself as a bot or as browser traffic is inconsistent
- The proportion of answers grounded in training data vs. real-time retrieval is not documented
- How DeepSeek weights authority signals during source evaluation is not published
DeepSeek vs Traditional Search
The same question, two completely different systems.
| Google Search | DeepSeek | |
|---|---|---|
| What the user sees | List of 10 links | Visible reasoning chain + cited answer |
| Reasoning visibility | None — black box | Full chain of thought exposed |
| Retrieval order | Index lookup, then ranking | Reason first, then retrieve |
| Crawler transparency | Documented user-agents | DeepSeekBot observed but undocumented |
| Citation format | Blue links in SERP | Inline within answer prose |
| Content type favoured | Authority + relevance | Structured, factual, contradiction-friendly |
| Primary visibility lever | Backlinks + technical SEO | Training-data presence + structured content |
| Downstream reach | Limited to search users | Open-source model powers thousands of downstream products |
Google SEO and DeepSeek GEO are not the same discipline. A page ranking #1 on Google for a query may not appear at all in DeepSeek's answer to the same query — and vice versa. Both require investment. Neither substitutes for the other.
Practical implications
What this means for your brand's visibility
Five implications derived directly from DeepSeek's confirmed architecture.
1. Training-data presence is the primary visibility lever
Because retrieval-time fetching is opaque and crawler compliance is unverified, the practical path to DeepSeek visibility runs through being present in DeepSeek's training data. This favours brands with strong Wikipedia entries, Crunchbase profiles, GitHub presence, academic citations, and earned press in publications DeepSeek likely sampled before training cutoffs.
Source: DeepSeek model release notes + third-party crawler observation, 2025-2026
2. Structured content outperforms marketing copy
DeepSeek's strength is reasoning over structured, factual content. Comparison tables, specification grids, technical documentation, and data-rich pages perform better than narrative-style brand pages. For B2B SaaS especially, product comparison pages and feature matrices are DeepSeek-native content formats.
Source: Reasoning chain analysis across DeepThink outputs, third-party reviewers
3. France-market brands have a present-day citation opportunity
With ~3-4% of DeepSeek's user base in France and a population already exposed to DeepSeek through downstream products, French-market brands have a citation opportunity their competitors are mostly ignoring. The first French B2B brands to systematically track DeepSeek visibility will compound a measurement advantage for the next 12-18 months.
Source: DeepSeek MAU geographic distribution, third-party app analytics 2025-2026
4. Technical content ranks disproportionately well
DeepSeek-Coder ranks #2 on Stack Overflow's coding-assistant preference survey. DeepSeek-R1 leads on math benchmarks. Technical content — clean code blocks, complete examples, proper syntax highlighting, mathematical notation — performs disproportionately well. For developer-tool brands, DeepSeek is potentially the highest-leverage visibility channel after ChatGPT.
Source: Stack Overflow Developer Survey 2025 + DeepSeek model benchmarks
5. DeepThink is a free competitive intelligence tool
Brands can use DeepThink mode to audit their own content. Asking DeepSeek to evaluate your category, and reading the visible reasoning chain, reveals which sources DeepSeek considers authoritative — and where your brand sits in that hierarchy. Few other engines expose this. Treat DeepThink as a free competitive intelligence tool.
Source: DeepThink product feature, deepseek.com
Frequently asked questions about DeepSeek
Is DeepSeek banned in France?
Does DeepSeek respect robots.txt?
How is DeepSeek visibility tracked?
Will my ChatGPT visibility predict DeepSeek visibility?
What is DeepThink and how does it differ from regular DeepSeek?
Sources cited on this page
Every factual claim on this page is sourced. We link to primary sources directly.
- DeepSeek — Official model release notes (V3, R1, V4 Preview) — 2024-2026 [source] Official documentation
- BrightEdge — The Ultimate guide to DeepSeek — 2025 [source] industry-analysis
- DataDome — AI Crawler Tracker (DeepSeekBot) — 2025-2026 [source] third-party-crawler-tracker
- ai.robots.txt — Community-maintained AI crawler directory — 2025-2026 [source] third-party-crawler-tracker
- Stack Overflow Developer Survey 2025 — AI assistant rankings — 2025 [source] industry-survey
- DeepSeek-V3 Technical Report (training cost disclosure) — December 2024 [source] Academic paper
Other AI search engines
The world's most used AI — and why it plays by completely different rules than Perplexity
Read deep dive → ClaudeThe reasoning engine that searches when it needs to — not by default
Read deep dive → Google GeminiOne model, many surfaces — and one robots.txt tag that determines if your brand gets cited
Read deep dive → Google AI OverviewsThe AI feature that reaches more people than any other product in the world
Read deep dive → GrokThe only AI engine trained on real-time social media data — and what that means for your brand
Read deep dive → Meta AIThe largest-scale consumer AI on the planet — and the cleanest robots.txt control surface in the ecosystem
Read deep dive → Microsoft CopilotThe only AI engine that retrieves from both the public web and your organization's private data
Read deep dive → Mistral Le ChatThe European AI engine — built in Paris, citing every source, embedded in Firefox
Read deep dive → Perplexity AIThe answer engine that cites its sources
Read deep dive →Does your brand appear when your prospects ask DeepSeek about what you do?
Most brands don't know. Storyzee runs systematic prompt testing across Perplexity, ChatGPT, Gemini and Claude — and turns the results into a score out of 100 with a prioritized action plan.