Gigantics provides a data security platform that automates the discovery, classification, transformation, and provisioning of sensitive datasets across cloud, on‑premises, and non‑production environments. Using AI‑driven scanning and a centralized policy engine, it masks, anonymizes or synthesizes data while preserving referential integrity, delivering versioned, audit‑ready datasets on demand for CI/CD pipelines, testing, and AI training.
Funding
Funding not disclosed
Founders
Product
Problem
Organizations handling sensitive data across cloud, on‑premises, and non‑production environments often rely on manual processes to copy, mask, or synthesize datasets. This manual handling creates bottlenecks in CI/CD pipelines, increases the risk of data leaks, and makes it difficult to demonstrate regulatory compliance.
Solution
Gigantics offers a data security platform that automates the full lifecycle of sensitive data—from discovery and classification to transformation and secure provisioning. The system connects to a wide range of database types, uses AI‑driven scanning to identify personal and regulated information, and applies policy‑based anonymization, masking, or synthetic data generation while preserving referential integrity. Transformed datasets are versioned and delivered on demand to any target environment, with full traceability and audit‑ready evidence that align with standards such as GDPR, HIPAA, NIS2, and ISO 27001. Integration hooks for CI/CD tools enable continuous delivery of compliant data, reducing provisioning time and minimizing exposure risk.
Target Audience
Primary customers are data‑centric DevOps teams, data architects, and compliance officers in regulated industries who need secure, automated data provisioning for development, testing, and AI model training across hybrid environments.
Features
- AI‑powered sensitive data discovery that tags and classifies PII across supported databases
- Centralized policy engine for rule‑based anonymization, masking, and synthetic data generation
- Generation of versioned, referentially intact datasets that maintain cross‑table relationships
- Automated provisioning of transformed data in SQL, JSON, or CSV formats to any configured environment
- CI/CD integration for on‑demand data delivery within deployment pipelines
- Full audit trail with change tracking, run IDs, timestamps, and exportable compliance reports
- Support for a broad spectrum of data sources, from open‑source and cloud databases to enterprise and big‑data platforms