Real ChatGPT answer · index seedv9fKXFMZB1scompleteB2B software · AI and automation toolsinformational
What steps should I take to fix poor vector search accuracy in our internal knowledge base chatbot this week?
Download run
Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
What steps should I take to fix poor vector search accuracy in our internal knowledge base chatbot this week?
1 real search · 1 real-search pass
2026 RAG retrieval evaluation Recall@K MRR nDCG hybrid search reranking best practices documentationGoogle ↗
OBSERVEDComparison
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
ChatGPT real searches (1)
Classes come from the query-classifier (a local Laya model). 1 of 1 calls are low-confidence (under 50%) — hover a query in the table to see its confidence.
Searches and sources
ChatGPT1 real searches · gpt-6
2026 RAG retrieval evaluation Recall@K MRR nDCG hybrid search reranking best practices documentation Google ↗
- architecture-center/docs/ai-ml/guide/rag/rag-information-retrieval.md at main · MicrosoftDocs/architecture-center · github.com
- AI Search retrieval quality guide - Azure Databricks · learn.microsoft.com
- Evaluate AI Search retrieval quality · docs.databricks.com
- Retrieval-Augmented Generation (RAG) Evaluators for Generative AI - Microsoft Foundry · learn.microsoft.com
- reranker (Reranker) · huggingface.co