The startup offers a data protection and security platform that enables real-time access to data without the need for data movement or duplication, ensuring compliance with data governance policies. This solution effectively manages data access across diverse environments, including cloud technology and AI projects, while maintaining security and reducing operational costs.
Funding
$7M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Organizations face increasing challenges in securing sensitive data while enabling real-time access for AI, analytics, and application workflows. Traditional data protection methods often involve data movement and duplication, creating silos, increasing operational costs, and raising the risk of data breaches and compliance violations. Existing solutions lack the granularity and real-time enforcement needed to govern data access effectively across diverse environments.
Solution
Dymium provides a just-in-time data access layer that governs data access in real time without requiring data copies or movement. The platform intercepts and governs every data request, applying policies based on identity, context, and policy at the moment of access. Dymium connects directly to live data sources, enforcing granular access controls at the field and row level, ensuring that users, AI agents, and applications receive only the data they need. This approach eliminates unnecessary data exposure, reduces the risk of breaches, and simplifies compliance with regulations like GDPR, HIPAA, and the EU AI Act.
Target Audience
Dymium targets data and AI teams, security and risk teams, and privacy and compliance teams that need to enable secure, governed data access for AI, analytics, and application workflows.
Features
- Real-time data access governance without data replication or staging
- Fine-grained access control at the field, row, and column level
- Policy enforcement based on user identity, context, and role
- Integration with existing data sources via mTLS with automatic metadata synchronization
- Support for AI/ML use cases, including secure access for LLMs and GenAI models
- Automated masking, redaction, and filtering of sensitive data
- Comprehensive audit logging of all data access requests and transformations
- Real-time compliance with GDPR, HIPAA, and EU AI Act