Public AI visibility scan
7/10 overall — Qdrant is named in 14 of 20 buyer Conversations. Strong presence, with Milvus as the closest rival named.
Each Surface ran the same five buyer Conversations. The Score below is mentions out of total Conversations.
Each Conversation is a buyer question a real prospect in the open-source vector database for AI applications category could ask. We send the same question to each Surface (ChatGPT, Claude, Perplexity, Gemini) and check whether Qdrant is named in the answer.
An overall Score of 7/10 means Qdrant was named in roughly 14 of 20 total Conversations across the four Surfaces. The named villain in their category is Milvus, which appeared in 20 of 20 Conversations. The Surface with the largest Gap is ChatGPT.
A selection of the actual buyer questions and what each Surface answered. Prompts and responses are truncated for readability. The full raw JSON is linked at the bottom of this page.
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For a **B2B SaaS team**, the best *general-purpose* open-source vector database is usually **Qdrant** if you want the strongest balance of **production readiness, fast performance, and flexible metadata filtering**.[6][…
What is the best open-source vector database for AI applications platform for a B2B SaaS team?
Choosing the best open-source vector database for AI applications in a B2B SaaS context depends on several factors, including scalability, ease of integration, performance, and community support. Here are some of the to…
Bersyn diagnoses why a brand is omitted on each Surface and generates corrective Patches anchored to attested Product Identity. Two ways to start:
Verify these results on your own account. The first scan is free and takes about two minutes.
One-time audit covering Gap diagnosis on each Surface plus copy-pasteable Patches you can ship immediately.
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