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AI Traffic Safety Gateway

Secure enterprise AI usage without disrupting employees.

Siyaj sits between employees and public AI tools to inspect AI-bound traffic, detect sensitive patterns, apply policy decisions, and create safe audit evidence for security teams.

Private technical preview · Local-first evaluation · No source code distribution.

01
AI Traffic
Inspected before reaching public AI tools
02
Policy Actions
Allow · Block · Redact · Warn · Log
03
Safe Evidence
Audit trail without exposing sensitive content
04
Local Preview
Time-limited controlled evaluation

The Problem

AI adoption is moving faster than enterprise controls.

Employees are already using public AI tools. Blocking AI slows productivity, but unmanaged usage can expose secrets, credentials, internal data, and sensitive business context.

Secrets pasted into AI tools, No visibility into AI usage, Traditional DLP is not prompt-aware, Browser extensions do not fit every environment, Security teams need safe audit evidence.

How Siyaj works in 3 steps
1

Connect

Traffic flows through the organization's approved proxy or SWG path.

2

Inspect

Siyaj inspects AI-bound traffic for secrets, credentials, sensitive patterns, and prompt risk.

3

Govern

Siyaj applies policy decisions and records safe audit evidence for security teams.

The Stack

What Siyaj adds to your AI traffic path.

Four focused layers that sit alongside your existing enterprise network controls.

Traffic Layer

  • Proxy / SWG path
  • ICAP inspection
  • AI provider classification

Detection Layer

  • API keys
  • Private keys
  • Credentials
  • Sensitive patterns
  • Prompt risk

Policy Layer

  • Allow
  • Block
  • Redact
  • Warn
  • Log

Evidence Layer

  • Audit log
  • Risk score
  • Signal type
  • Provider
  • Timestamp
  • Outcome
  • Notification status

Capabilities

Siyaj capabilities

A complete safety layer for governing public AI usage — from traffic inspection and policy decisions to audit evidence and private preview operations.

AI Traffic Inspection

Inspect AI-bound traffic · Proxy / SWG path support · ICAP-style inspection model · Public AI destination classification · Prompt / file / API request awareness

Secret & Sensitive Pattern Detection

API key detection · Private key detection · Credential pattern detection · Sensitive data pattern detection · Prompt risk signals · Configurable detection rules

Policy Decisions

Allow · Block · Redact · Warn · Log only · Monitor-first evaluation mode

Safe Audit Evidence

Decision record · Signal type · Risk score · Provider / destination · Timestamp · Outcome · Notification status · Metadata-first audit trail

Security Team Visibility

Read-only dashboard · Recent events view · Provider traffic view · Policy outcome visibility · POC evidence view · Safe screenshots guidance

Private Preview Operations

Local Preview Manager · Signed trial license · Time-limited evaluation · One-command local stack direction · Doctor / status checks · Install instructions · No source code distribution

Built to support the full journey: discover AI usage → inspect risk → apply policy → record safe evidence → evaluate locally.

Architecture

How Siyaj works.

A single inspection and policy layer between the employee and the public AI tool.

AI Traffic Safety Gateway · System BlueprintArchitecture
1
Employee Browser
Normal employee workflow
2
Organization Proxy / SWG
Approved traffic path
3
Siyaj ICAP Inspection
Detect secrets, sensitive patterns, and AI risk
4
Policy Engine
Apply organization rules
5
Decision
ALLOW / BLOCK / REDACT / WARN / LOG
6
Public AI Tools
AI provider destination
Safe Audit Log
Decision, signal, risk score, provider, timestamp, outcome
Dashboard Evidence
Security team visibility
Request path
Policy decision
Audit evidence

In Real Usage

What happens when an employee uses AI?

Five steps. No new login. No browser extension required.

  1. 1Employee uses AI normally
  2. 2Traffic passes through the organization path
  3. 3Siyaj inspects risk signals
  4. 4Policy action is applied
  5. 5Audit evidence is recorded

Business Outcomes

What your organization gains.

Business-first results for safer AI adoption.

Safer AI adoption

Enable public AI usage with a safety layer in front of it.

Lower secret leakage risk

Detect and stop API keys, tokens, and credentials before they leave.

Better security visibility

See how public AI is being used through safe operational metadata.

Policy-based control

Allow, block, redact, warn, or log — by provider, group, or risk.

Employee workflow continuity

Employees keep using the tools and habits they already have.

Audit-ready governance

A continuous, safe evidence trail for security and compliance teams.

Private Preview

What the private preview includes.

A controlled, time-limited package to evaluate Siyaj locally.

  • Local Preview Manager
  • One-command local setup
  • Read-only dashboard
  • Secret blocking demo
  • Redaction demo
  • Safe audit evidence view
  • Doctor / status checks
  • Time-limited signed trial license
  • No source code distribution

Private preview is for controlled evaluation with synthetic or approved test data.

Apply as a design partner

Request access to the private technical preview and evaluate Siyaj in a controlled local environment.

Security and Leadership

Built for teams responsible for AI risk.

Practical outcomes for the people who carry AI risk and AI adoption.

For Security Teams

  • Detect risky AI usage
  • Investigate events with safe evidence
  • Reduce secret leakage risk
  • Prepare for future SIEM and notification paths

For Technology Leaders

  • Enable AI adoption responsibly
  • Avoid blocking productivity
  • Build governance around public AI usage
  • Evaluate locally before rollout

Built for governed AI adoption

Designed with governance, auditability, and risk-management principles aligned with frameworks such as NIST AI RMF and ISO 27001-style control thinking.

FAQ

Common questions.

Get Access

Ready to evaluate safer AI adoption?

Request access to the private technical preview and evaluate Siyaj in a controlled local environment.

We only use this information to evaluate preview requests.