Add Value Machines provides a platform that implements role-based access controls, audit logging, and prompt policies to secure generative AI models within enterprise environments. This solution ensures compliance with data protection regulations by enabling organizations to safely utilize their sensitive data while maintaining full control and observability over AI interactions.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises face security and compliance risks when using generative AI models like ChatGPT, as these models are trained on vast amounts of data, including potentially sensitive user information. Data leaks, unauthorized access, and non-compliance with regulations like PII, PCI, and PHI are major concerns.
Solution
Add Value Machines (AVM) provides a secure GenAI operating system that enables enterprises to leverage generative AI applications while maintaining full control and observability over data. The platform implements role-based access controls, prompt policies, and audit logging to ensure compliance with data protection regulations. AVM integrates with existing systems and IDP providers, offering features like data encryption, compliance checks, and the ability to redact or block sensitive information. The solution is model-agnostic and can be deployed on major cloud providers, allowing organizations to use the best model for their specific use case without being locked into a single provider.
Target Audience
AVM's primary customers are enterprises in regulated industries such as finance, healthcare, and insurance, as well as any organization that handles sensitive data and requires secure, compliant AI solutions.
Features
- Role-based access controls to manage user permissions and data access
- Prompt policies to govern AI interactions and prevent misuse
- Audit logging to track all AI usage and ensure compliance
- Integration with IDP providers (Google, Azure, Cognito) for secure authentication
- Integration with document providers (GDrive, S3) for data access
- Integration with SIEM providers (Splunk) for security monitoring
- Data encryption at rest and in transit to protect sensitive information
- Compliance checks for PII, PCI, and PHI data
- Model-agnostic architecture to support various foundation models
- Deployment on major cloud providers (AWS, Azure, GCP)