Scalable Real-time Analytics

Bolt's scalable high performance analytical engine provides a powerful set of deep learning and machine learning models, allowing our customers to analyze data in innovative ways to significantly reduce time to identify and resolve issues.

Models include:

Univariate Anomaly Detection

Multivariate Anomaly Detection


The open, pluggable architecture supports integration of third party and in-house developed models to allow customers to create flexible solutions. The containerized architecture consisting of models and model orchestration allows for flexible deployment in the cloud or on-premises.

To connect data to the models, intelligent connectors enable quick and easy addition of data sources.

Bolt Intelligent Ingestion Architecture

Scalable: Tested to ingest up to 6 TB of data daily
Extensible: New data sources for ingestion can be added in hours
Pipelined: Allows data to be manipulated and cleansed for analysis

Bolt Analytics Architecture

Flexible: Use CPU’s or GPU’s for training
Manage: Train, Infer, and manage multiple models in parallel
Unique: Time series models that detect and predict on single or multiple variables