How do we implement rate limiting and cost controls per tenant in a multi-tenant B2B SaaS application that exposes AI features via API?
Download run
Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
How do we implement rate limiting and cost controls per tenant in a multi-tenant B2B SaaS application that exposes AI features via API?
3 real searches · 1 real-search pass
Redis token bucket rate limiting official documentation Lua scripts atomic operationsGoogle ↗
OBSERVEDReason
AWS SaaS tenant isolation tenant context best practices official architectureGoogle ↗
OBSERVEDComparison
OpenAI API usage costs token usage pricing official documentationGoogle ↗
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
Queries
3 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
Redis token bucket rate limiting official documentation Lua scripts atomic operations OBSERVED | Google ↗ AI Mode ↗ | — | Reason | — | — | 1x of 1 | |
AWS SaaS tenant isolation tenant context best practices official architecture OBSERVED | Google ↗ AI Mode ↗ | — | Comparison | — | — | 1x of 1 | |
OpenAI API usage costs token usage pricing official documentation OBSERVED | Google ↗ AI Mode ↗ | — | Other / navigational | — | — | 1x of 1 |