I need a simple guide on integrating LLMs with Slack because my team spends too much time searching for internal documents.
Download run
Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
I need a simple guide on integrating LLMs with Slack because my team spends too much time searching for internal 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.
ChatGPT real searches (2)
Classes come from the query-classifier (a local Laya model). 1 of 2 calls are low-confidence (under 50%) — hover a query in the table to see its confidence.
Searches and sources
ChatGPT2 real searches · gpt-6
Slack API documentation Events API slash commands bot messages official docs 2026 Google ↗
OpenAI API embeddings file search vector stores official documentation retrieval augmented generation Google ↗
- Slack Events API documentation · docs.slack.dev
- OpenAI File Search documentation · developers.openai.com
- OpenAI Retrieval guide · developers.openai.com
- Slack API Apps · api.slack.com
- Implementing slash commands · docs.slack.dev
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
Slack API documentation Events API slash commands bot messages official docs 2026 OBSERVED | Google ↗ AI Mode ↗ | — | Other / navigational | — | — | 1x of 1 | |
OpenAI API embeddings file search vector stores official documentation retrieval augmented generation OBSERVED | Google ↗ AI Mode ↗ | — | Other / navigational | — | — | 1x of 1 |