HubVibe
Anomaly detection on a time series: score recent periods against history with BigQuery AI.DETECT_ANOMALIES (TimesFM). Give one table and its latest periods are scored against its own history, or a history and a target table. Returns every c
Go to this service →Our latest check (2026-10-11)
- Answering
- Yes — valid x402 payment terms
- Time to answer
- 275 ms
- Price
- $10.000 per call
- Paying buyers, last 30 days
- 1 (directory's own records)
- Paid calls, last 30 days
- 3
- Category
- Unclassified
- Address
- https://hubvibe-io.com/work/data/anomalies
Accuracy: paid answers checked against an independent record
Not yet in our paid checks. A seller we have not checked has neither passed nor failed.
For agents
This page as JSON: /sellers/8537bb9005c6.json. Paid lookup by address: GET /api/seller?resource=… ($0.001, x402).