Securing GenAI with SecuPi DSP
The New Security Challenge: When AI Meets Enterprise Data
Generative AI changes how organizations use data and how data escapes. Modern AI applications do not just read dashboards or APIs. They tap into multiple structured and unstructured data sources such as databases, data lakes, and collaboration tools, and start pulling information at machine speed.
These sources were built to control user access. They were never designed to control AI access.
Once an LLM based application is connected, it can ingest, cache, and reproduce sensitive data far beyond intended boundaries, often with no visibility, no policy enforcement, and no audit trail. And when that data is also used for model training, the risk multiplies. Sensitive content can reappear as part of future AI responses.
The Core Problem
- Multiple access paths: AI apps pull data from several repositories simultaneously, bypassing traditional access controls.
- Blurred accountability: AI agents and pipelines act as non-human identities with unclear permissions.
- Continuous training needs: Models require access to sensitive data for fine-tuning, yet enterprises must ensure no unauthorized exposure.
- No unified visibility: Security and compliance teams cannot trace which AI process accessed what data, when, or for what purpose.
The SecuPi Approach: ABAC for AI
SecuPi brings Attribute-based Access Control (ABAC) and data-centric protection directly into the GenAI workflow. Instead of locking data away, SecuPi enables safe data usage across every AI pipeline, from ingestion to inference.
How it works:
- Data-aware Policies: Access decisions are enforced at query time, based on data classification, user identity, AI model, and context.
- Fine-grained Controls: Dynamic masking, anonymization, and filtering ensure only the right data is exposed for each AI task.
- End-to-end Monitoring: Every AI data request is traced, audited, and governed through a unified policy layer across databases, files, and APIs.
- On-premise or Hybrid: SecuPi integrates seamlessly with on-premise and cloud-based AI frameworks, supporting both local LLMs and external AI connectors.
Why SecuPi Is Different
| Challenge | Other AI Security | SecuPi DSP |
|---|---|---|
| Data Access | Coarse grained, static permissions | Fine grained, contextual ABAC across all sources |
| AI Training | Block or allow only | Governed exposure with anonymization, masking, conditional use |
| Visibility | Limited to app layer | Full audit across data, user, and AI pipeline |
| Integration | Per app customization | Unified control layer across structured and unstructured data |
| Deployment | Cloud only or isolated | On premise, hybrid, or multi cloud where your data never leaves control |
SecuPi: Secure AI Without Stopping Innovation
AI thrives on data. But data must remain protected even when machines are the ones asking for it. With SecuPi DSP, organizations can securely enable GenAI adoption while maintaining full control over who or what accesses their sensitive data. Empower your teams to innovate with confidence without exposing your crown jewels.
Schedule a demo to see how SecuPi keeps your AI data aware, compliant, and secure.