Real ChatGPT answer · index seedWkjhyrz3g14completeMarketing and advertising · AI search and generative engine optimizationinformational
What are the concrete steps required to optimize our company website for multimodal search where users upload images and text together?
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Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
What are the concrete steps required to optimize our company website for multimodal search where users upload images and text together?
3 real searches · 1 real-search pass
multimodal search image text joint query website architecture CLIP embeddings hybrid search best practices 2025 2026Google ↗
OBSERVEDOther / navigational
Google Vertex AI multimodal embeddings image text documentation vector searchGoogle ↗
OBSERVEDOther / navigational
OpenAI image input embeddings visual search API documentation image text retrievalGoogle ↗
OBSERVEDOther / navigational
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 (3)
Classes come from the query-classifier (a local Laya model). 3 of 3 calls are low-confidence (under 50%) — hover a query in the table to see its confidence.
Searches and sources
ChatGPT3 real searches · gpt-6
multimodal search image text joint query website architecture CLIP embeddings hybrid search best practices 2025 2026 Google ↗
Google Vertex AI multimodal embeddings image text documentation vector search Google ↗
OpenAI image input embeddings visual search API documentation image text retrieval Google ↗
- Hybrid Search Overview - Azure AI Search · learn.microsoft.com
- Build a multimodal search engine with Vertex AI combining text and image · cloud.google.com
- Multimodal Search Concepts and Guidance - Azure AI Search · learn.microsoft.com
- Embeddings | Gemini API | Google AI for Developers · ai.google.dev
- Gemini Embedding 2 model | Gemini API | Google AI for Developers · ai.google.dev
- Building with Gemini Embedding 2: Agentic multimodal RAG and beyond · developers.googleblog.com
Queries
3 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
multimodal search image text joint query website architecture CLIP embeddings hybrid search best practices 2025 2026 OBSERVED | Google ↗ AI Mode ↗ | — | Other / navigational | — | — | 1x of 1 | |
Google Vertex AI multimodal embeddings image text documentation vector search OBSERVED | Google ↗ AI Mode ↗ | — | Other / navigational | — | — | 1x of 1 | |
OpenAI image input embeddings visual search API documentation image text retrieval OBSERVED | Google ↗ AI Mode ↗ | — | Other / navigational | — | — | 1x of 1 |