Introduction
Sensitive data leakage concerns are growing, especially in the AI-agentic world, where data flows are complex and hard to control. Even with local hosting, modern stacks constantly move data across systems and vendors. For enterprises, this isn't just a privacy and compliance challenge. It's becoming a brake on innovation, leaving valuable data unexploited.
What is Quba?
Quba is a solution that automatically scans and anonymizes sensitive data in your trusted environment, replacing it with reversible tokens, and the data is only unanonymized when results are returned, keeping it protected at every step.
Use cases
| Use case | Description |
|---|---|
| Data Processing | Process sensitive data securely by detecting, masking, and replacing it with reversible tokens. Data remains masked when leaving your trusted environment and is unmasked only when results return. Keeping it safe at every step. |
| AI Training | Automatically mask all training datasets before sharing them with researchers, partners, or the public, ensuring privacy and compliance at scale. |
| AI Agent Security (MCP Gateway) | Protect sensitive data when employees share data with MCPs by routing all traffic through a centralized MCP proxy, ensuring control, visibility, and compliance across your organization. |
| Integration with Existing Systems | Protect sensitive data when employees interact with AI or communicate with customers, whether through customer care systems, patient portals, or other channels, ensuring privacy and compliance at every touchpoint. |
The Control Layer
Quba gives you per-field, per-use-case control over how sensitive data is handled, letting you choose the best approach for each situation.
| Method | What happens | Best for |
|---|---|---|
| Mask | Value is hidden or obscured in place | Logs, audit trails, internal review |
| Redact | Value is removed entirely | Legal documents, compliance exports |
| Replace | Swapped with a realistic synthetic value | AI training, testing, analytics |
The right method depends on what the data will be used for.