NeuralDLP

The security layer AI agents need

AI agents are transforming how organizations operate. But every agent that touches sensitive data creates a new attack surface. NeuralDLP exists to close that gap.

The problem

AI agents process customer data, internal documents, and credentials as part of normal operation.

Prompts containing PII, API keys, or confidential information are sent to third-party LLM providers.

There is no standard security checkpoint between an agent workflow and the models it calls.

Compliance teams cannot audit what data flowed through which model, when, or why.

Our approach

Inline, not sidecar

NeuralDLP sits directly in the execution path. A single API call before the LLM gives you classification, enforcement, and routing with under 200ms overhead.

Policy-driven, not heuristic

Define explicit rules for what happens when sensitive data is detected. No black boxes. Policies are versioned, auditable, and testable.

Tenant-aware by default

Built for multi-tenant platforms. Provision organizations programmatically, isolate policies and rate limits, and deprovision with GDPR-compliant data cleanup.

Technology

Python / FastAPI async API
spaCy NLP for entity recognition
AES-256 tokenization engine
PostgreSQL for audit persistence
Redis for decision caching
AWS App Runner with auto-scaling

Want to learn more?

Read the API documentation or create a free account to start testing.