Your Data
Stack Deserves Technology From The Future

TensorStax uses autonomous AI to not just visualize or monitor pipelines, but to actively build, optimize, and maintain them. It integrates directly with your stack (like dbt, Spark or Airflow) and generates production-ready pipelines, with customization and version control out of the box.

TensorStax is also fully aware of your schemas, infrastructure and has context on how how you prefer to structure your pipelines.

No. TensorStax never stores or accesses your raw data. It operates on pipeline metadata and code, ensuring your sensitive data stays within your infrastructure.

Yes. TensorStax supports self-hosted deployments in your private cloud or VPC, giving you full control over infrastructure and data governance.

Yes. TensorStax follows enterprise-grade security practices, including SOC 2, GDPR, RBAC, and audit logging. We ensure secure data handling and full compliance with industry requirements.

TensorStax integrates seamlessly with dbt, Apache Airflow, GitHub, GitLab, and is compatible with most modern data warehouses and lakehouses like Snowflake, BigQuery, Redshift, and Databricks.

TensorStax continuously analyzes pipeline logic and runtime behavior. It uses AI to detect errors, anomalies, and anti-patterns, and can automatically suggest or apply fixes through pull requests or in-product suggestions.

Absolutely. You can define custom rules, manually edit AI-generated code, and review everything via GitHub or GitLab PRs. TensorStax gives you full control over how pipelines are created and optimized.