Why are my vector embeddings failing to find the right context and what troubleshooting steps should I take to improve search relevance
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Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
Why are my vector embeddings failing to find the right context and what troubleshooting steps should I take to improve search relevance
1 real search · 1 real-search pass
vector embeddings retrieval relevance troubleshooting chunking hybrid search reranking evaluation official documentation OpenAI Pinecone 2026Google ↗
OBSERVED
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.
Classifying 1 queries…
Searches and sources
ChatGPT1 real searches · gpt-6
vector embeddings retrieval relevance troubleshooting chunking hybrid search reranking evaluation official documentation OpenAI Pinecone 2026 Google ↗
- Retrieval-Augmented Generation (RAG) · pinecone.io
- RAG Debugging Guide: Fix Retrieval Errors Fast · redis.io
- Rerankers and Two-Stage Retrieval · pinecone.io
- architecture-center/docs/ai-ml/guide/rag/rag-information-retrieval.md at main · MicrosoftDocs/architecture-center · github.com
- Evaluate AI Search retrieval quality - Azure Databricks · learn.microsoft.com
- Troubleshooting Knowledge Retrieval for Agents · help.salesforce.com