We need to integrate an LLM with Slack for internal IT help, but I need to keep API token costs under control.
Download run
Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
We need to integrate an LLM with Slack for internal IT help, but I need to keep API token costs under control.
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
Slack AI helpdesk bot architecture cost optimization caching RAG token usage Slack app official documentation Google ↗
OpenAI API pricing prompt caching batch embeddings official 2026 Google ↗
- Context management · docs.slack.dev
- Data & security best practices for agentic Slack apps | Blog · slack.dev
- Pricing · developers.openai.com
- Security for AI features in Slack · slack.com
- Work with AI agents in Slack · slack.com
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
Slack AI helpdesk bot architecture cost optimization caching RAG token usage Slack app official documentation OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 | |
OpenAI API pricing prompt caching batch embeddings official 2026 OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 |