SliceUp delivers an anomaly detection eco-system using an in-memory, lightning fast, time-series database to analyze and downsample unstructured data on the edge and powerfully robust to build ML/DL models in the cloud.

Key Features

Multiple ML/DL Models Working Together

Multi-dimensional, supervised and semi-supervised ML/DL models bring anomaly detection to the edge and allows powerful and comprehensive models to be deployed to the cloud

Easy Ingestion

Most data sources are supported including all metrics and logs

Auto Log Parsing

Supports semi and unstructured logs files by discovering patterns and creating structured data

Real Time Analytics

Access data in real time including anomaly detection and Automated Root Cause Analysis (ARCA)


Easily integrate your existing data sources and alerting tools

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