Anomaly Detection engines in the Veritone cognitive engine ecosystem assign a confidence value to specific entries in time-series data sets with the goal of predicting which events are anomalous.
Simply ingest time-series data that gives the engine a list of numbers representing certain events and corresponding timestamps of when they occurred. The engine will process this and return the likelihood that any given event is anomalous.
Anomaly Detection Features:
- Flexible Deployment
Deploy in a new or integrate into an existing application in the cloud via aiWARE GraphQL APIs, or with a subset that can be deployed on-premise via a Docker container. Learn more.
- Powered by an AI Ecosystem
Leverage advanced anomaly detection machine learning algorithms from the Veritone managed cognitive engine ecosystem — including algorithms from Veritone, niche providers, and industry giants.