Eliminate downtime

Monitor enterprise data across data lakes, warehouses, and other repositories to eliminate issues that impact reliability.

Scale workloads

Ensure availability for mission-critical data and workloads.

Automate validation

Classify, catalog, and manage business rules for data at rest and data in motion.

Acceldata Torch uses advanced machine learning and AI to automate data quality and reliability for enterprise data systems, regardless of scale, number of sources, and complexity of data types and structures.

Go beyond data monitoring

  • Automate taxonomy of sensitive and related data assets
  • Reconcile data in motion and during cloud migrations
  • Detect schema and data drift to improve dynamic data handling and ML and AI accuracy

Automate data discovery, exploration, and validation

  • Discover data rapidly with self-service data catalogs
  • Explore data profiles and metadata quickly across the entire enterprise environment
  • Improve data trust by increasing data transparency and creating data community
Intelligent Data

Validate data quickly at scale

  • Improve data context with ML-based classification, clustering, and association
  • Apply ML-driven recommendations to improve data quality accuracy, coverage, and efficiency
  • Automate data governance across your enterprise data environments whether on-prem, hybrid, or in the cloud

Torch integrates with your most critical data systems

Apache HBase
Mysql
Databricks
Google Cloud Storage
Snowflake
Portrait of Rohit Choudhary

Rohit Choudhary

Founder & Chief Executive Officer, Acceldata

“Automating data reliability and improving data access through our Data Observability Cloud will create powerful data network effects. Enterprises can support significantly more data use cases and data consumers, while accelerating their data-driven transformation.”

Ready to start your data observability journey?

Request a demo and chat with one of our experts.