Can you walk me through building a simple custom internal chatbot for our intranet using our existing employee handbook documents?
Download run
Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
Can you walk me through building a simple custom internal chatbot for our intranet using our existing employee handbook documents?
2 real searches · 1 real-search pass
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 2 queries…
Searches and sources
ChatGPT2 real searches · gpt-6
site:platform.openai.com/docs/guides/tools-file-search OpenAI File Search Responses API vector stores official docs Google ↗
site:openai.com/enterprise-privacy API data not used to train by default business data official Google ↗
- File search · developers.openai.com
- Data controls in the OpenAI platform · developers.openai.com
- Business data privacy, security, and compliance · openai.com
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
site:platform.openai.com/docs/guides/tools-file-search OpenAI File Search Responses API vector stores official docs OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 | |
site:openai.com/enterprise-privacy API data not used to train by default business data official OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 |