RAG explained: how AIs research before answering
Published on October 06, 2026
AEO and GEO Fundamentals
When ChatGPT answers "which dentist to recommend in [your city]", it isn't reciting a memorized list: it's researching on the spot. This technique is called RAG, short for retrieval-augmented generation, and it's the mechanism that makes the AI search for sources on the web before putting together its answer. Anyone who understands how RAG picks sources can, literally, write the answer the patient will receive.
At Bincoo, by monitoring thousands of clinics, we see RAG in action every day: the AI retrieves the same well-structured sources and turns them into recommendations.
More than 10,000 companies already use Bincoo to be recommended by ChatGPT, Gemini, and other platforms.
How RAG works, in clinic-owner language
The process has three stages, and each one is a chance to get into the answer:
- Retrieval: the AI turns the patient's question into a search and collects relevant pages, reviews, and mentions;
- Filtering: out of everything it retrieved, the model prioritizes sources that are clear, specific, and consistent with each other;
- Generation: the answer is written based on what survived, citing names, addresses, and specialties.
Practical translation: if your clinic isn't in the retrieved material, it doesn't exist in the answer. And if its data is contradictory, the model prefers the more consistent competitor.
Why the same question gets different answers
Clinic owners report that ChatGPT answers one thing on Monday and another on Thursday. That's RAG: since web search changes every day, the answer changes with it. New content published by a competitor, a fresh news story, new reviews — all of that changes what gets retrieved. The AI's answer is a snapshot of what the web says today, not an eternal sentence.
What RAG values in sources
| Signal in the source | Effect on the AI's answer |
|---|---|
| Service page with price and indication | Becomes a direct citation basis |
| Article answering a patient question | Becomes a quoted excerpt in the answer |
| Recent, responded-to reviews | Weighs in on who to recommend |
| Identical data across multiple channels | Confirms identity, prevents errors |
| Vague or outdated content | Ignored in favor of the competitor |
| Mention in an independent portal | Validates the clinic as a reference |
The 5 steps to get into the RAG pipeline
- Find out what's being retrieved today: ask the patients' questions to the AIs and note which sources show up in the answers;
- Fill the gaps: every service needs its own clear page, with indication, process, and price range;
- Publish questions with answers: the question-and-answer format is what RAG extracts most easily;
- Unify your data: same name, address, and phone on website, Google, directories, and social media;
- Monitor weekly: the pipeline changes every day, and whoever doesn't measure loses citations without noticing.
The most expensive mistake: letting the AI guess
When RAG can't find a clear source, it doesn't say "I don't know". It fills the gap with an assumption. That's how the clinic with the wrong address, the deactivated phone number, and the specialty you never offered come to be. The owner finds out when a patient calls asking about something else. The fix isn't to complain to the AI: it's to publish sources clear enough that it doesn't need to guess.
How Bincoo uses this to your advantage
Optimizing for RAG takes technique and cadence: identifying gaps, structuring answers, and publishing every week. Bincoo runs that cycle end to end for your clinic: it monitors what the AIs retrieve, generates the content plan, and publishes the articles that become the sources of the answers. On the Essential plan, at R$ 39,00/month, you already get the monitoring and weekly production.
Conclusion
- RAG is the mechanism that makes the AI search the web before answering, and it decides who shows up;
- Clear, specific, and consistent sources are what RAG retrieves and cites;
- Whoever leaves gaps lets the AI invent: publish so you don't get guessed at.
Want to know what RAG retrieves when people ask about your specialty? visit Bincoo and see your clinic's report.
Frequently asked questions
"What is RAG?"
RAG stands for retrieval-augmented generation, the technique that allows artificial intelligence to search external sources before answering. Instead of relying only on what it memorized during training, the AI looks up pages, reviews, and up-to-date mentions and writes its answer based on them.
"Does ChatGPT search the web on every question?"
Not on every one, but for local and commercial questions, such as which clinic to choose, web search is almost always triggered. That's precisely why content published today influences today's answer, without waiting months for indexing.
"How does RAG choose sources?"
The model turns the question into a search, collects the most relevant and trustworthy pages and mentions, and then writes the answer citing what it retrieved. Clear, specific sources that are consistent with each other are far more likely to be retrieved than vague pages.
"Does RAG explain why the AI makes up wrong information about my clinic?"
Yes. When it doesn't find clear sources about your clinic, the model fills in the gaps with what it assumes, and that's how wrong addresses, old phone numbers, and invented specialties are born. The fix is to publish clear, consistent sources, not to complain to the AI.
"Does Bincoo optimize my clinic for RAG?"
Yes. Bincoo understands what AIs retrieve about your specialty and city, points out source gaps, and publishes structured content weekly that becomes the raw material of the answers, starting at R$ 39,00/month on the Essential plan.
