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AI Data Security Platform

Secure every AI interaction

FastPII brings Detection Engine, Protection Engine, AI Gateway, Policy Engine, and Audit into one operating layer so teams can detect, protect, govern, and audit AI traffic without stitching together point tools.

Integrated modules

One control plane for AI data security

Core verbs

Detect, protect, govern, and audit.

Gateway path

OpenAI-compatible proxy with streaming and BYOK.

Five pillars

Five modules, one operating model

Each module handles a different control point, but they work as one system across prompt, response, agent, and workspace traffic.

Detect

Detection Engine

Run 33 detectors across Czechia, Poland, Germany, and France with checksum-aware validation for high-signal identifier coverage.

Protect

Protection Engine

Apply redact, mask, anonymise, or hash before any sensitive data reaches a model, log, or downstream workflow.

Govern

Policy Engine

Match policies by entity type, country, provider, model, workspace, confidence, and sensitivity, then enforce the right action.

Audit

Audit

Capture 20+ fields per event, export JSON or CSV, and generate review-ready report templates for compliance teams.

Connect

AI Gateway

Route OpenAI-compatible traffic through /v1/chat/completions with streaming, provider routing, BYOK, and central policy checks.

Architecture flow

How FastPII moves through every AI request

The platform is designed to sit in the path of live AI traffic so controls happen before data leaves your application boundary.

Step 1

Application request enters

Application request enters FastPII

Step 2

Detection Engine identifies

Detection Engine identifies sensitive data

Step 3

Protection Engine transforms

Protection Engine transforms what should not leave the organisation

Step 4

Policy Engine decides

Policy Engine decides ALLOW, WARN, MASK, BLOCK, ESCALATE, LOG, or QUARANTINE

Step 5

AI Gateway forwards

AI Gateway forwards the safe payload to the selected provider

Step 6

Audit records the

Audit records the decision and exportable evidence

Ready to deploy

Start with one use case, expand to every model path

Teams usually begin with prompt inspection, then roll out the same policies to chat, agents, SDK workloads, and central gateway traffic.