Retrieval Architecture
Check if ChatGPT and Perplexity can actually read your site
Retrieval Architecture launched on August 25, 2026 with 2 votes, #5,788 of 23,274 launches that month.
What it does
Retrieval Architecture is a technical GEO/AEO consultancy. Audit website architectures for RAG systems, passage retrieval, and Wikidata entities.
When ChatGPT, Perplexity, or Gemini answer a question about your product, they cite you or a competitor. I find the technical reasons your site gets skipped, how it renders, how it's structured, how your brand is identified, and fix them. AI engines don't rank pages by keywords anymore. They break your site into chunks, match those chunks by meaning, and check whether your brand is a recognized, disambiguated entity. Here's what that looks like in practice. Retrieval-Augmented Generation systems break documents into blocks. Clean DOM elements determine the quality of the generated vector embeddings. AI models associate product names and brands with standard knowledge databases (such as…from retrieval-architecture.vercel.app
Does a similar job
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We’ve trained a generative AI model to browse the web and answer questions/retrieve code snippets directly. Unlike ChatGPT, it has access to primary sources and is able to cite them when you hover over an answer (click on the text to go to the source being cited). We also show regular Bing results side-by-side with our AI answer. The model is an 11-billion parameter T5-derivative that has been fine-tuned on feedback given on hundreds of thousands of searches done (anonymously) on our platform. Giving the model web access lessens its burden to need to store a snapshot of human knowledge…
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Growth · 11d ago · wallhop.io
Source: Product Hunt launch ↗
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