EnterpriseFinancialPublic Sector

    Control Generative AI
    Across Every Organization

    FlowGuard detects and manages sensitive data exposure, Shadow AI usage, and policy violations across ChatGPT, Copilot, Claude, and 40+ AI services.

    Where we're going

    No Input. Still Leaked.

    Through MCP, AI connects straight into wikis, databases, ticketing systems, and code repositories and pulls data on its own. Prompt inspection sees none of it.

    Where we're going

    From Prompt Checks
    to Action Guardrails

    The control point is moving from what was typed to what the agent did. FlowGuard AI is extending the platform in exactly that direction.

    40+

    AI Services Monitored

    13,000+

    Shadow AI Database

    Real-time

    Detection & Blocking

    5 min

    Time to Deploy

    Compliance Infrastructure
    SOC 2 Type IIISO 27001GDPRHIPAA

    Two-stage control

    Cloud Application Control

    Who, and where to

    Blocks personal accounts and unapproved tenants, leaving only the approved corporate workspace.

    AI DLP

    And what gets sent

    Inside the approved tenant, sensitive data is still detected, masked or blocked, and logged.

    The Problem

    Uncontrolled AI Usage
    Threatens Enterprise Security

    The first wave of risk was what an employee typed. As AI connects into internal systems and calls tools on its own, what the AI did is becoming the new risk on top of it.

    01

    Sensitive Data Leakage

    Employees inadvertently submit PII, source code, trade secrets, and financial data to external AI services.

    02

    Shadow AI Usage

    Over 13,000 AI tools operate outside IT approval, with no security policy coverage or visibility.

    03

    Unenforceable Policies

    Policies like "don't enter confidential data into AI" cannot be enforced without technical controls.

    04

    No Security Visibility

    Security teams have no way to know which departments use which AI tools with what data.

    05

    New wave

    Agent Access to Internal Systems

    Through MCP, AI connects straight into wikis, databases, ticketing systems, and code repositories. Data moves even when nobody types anything sensitive.

    06

    New wave

    No Audit Trail for Tool Calls

    Without a record of which tools an agent invoked, with what arguments, and what it changed, neither incident analysis nor regulatory response is possible.

    How It Works

    FlowGuard Monitors and Controls
    AI Usage

    Warn or block sensitive data inputs per policy, and log every event in an auditable format. The four steps below are the control flow available today.

    1

    Detect & Visualize Usage

    Detect usage of 40+ AI services in real time, with visibility by department, user, and AI app.

    2

    Sensitive Data Detection

    Analyze AI inputs to detect PII, source code, financial data, and medical information in real time.

    3

    Policy-Based Control

    Warn or block sensitive inputs in real time. Policies apply at the organization, department, or user level.

    4

    Logging & Audit Reports

    Log all detection events and enforcement results for compliance audits and security analysis.

    Watch

    See FlowGuard in Action

    The brand film for the whole picture, the CAC + AI DLP film for how the account and the prompt get covered together.

    Product Demos

    Confidential Document Leak Detection

    Confidential Document Leak Detection

    Click to launch demo

    Sensitive Data Leak Detection

    Sensitive Data Leak Detection

    Click to launch demo

    Key Capabilities

    Six Security Capabilities Available Today

    Sensitive Data Detection

    Detects 130+ sensitive data types — PII, source code, financial data, medical information, and trade secrets — in real time.

    GenAI Input Monitoring

    Monitor actual inputs to 40+ AI services including ChatGPT, Claude, Gemini, Copilot, and Cursor.

    Policy-Based Control

    Apply granular security policies by organization, department, or user to automate warnings, blocking, and logging.

    Shadow AI Detection

    Detect 13,000+ AI tools used without IT approval and enforce allow/block policies across all of them.

    User & Dept Risk Analysis

    Analyze risk scores and detection events by user, department, and AI app to identify high-risk behavior patterns.

    Audit Logs & Reports

    Comprehensive reports on AI usage, sensitive data detection, policy violations, and user behavior analytics.

    Security Architecture

    Integrated Security Flow
    from Endpoint to Admin Console

    See where data is detected, how policy decisions are made, and where events are recorded.

    FlowGuard AI DLP 보안 아키텍처 — 라이트 모드

    Use Cases

    Built for Every Organization
    Handing AI More Work

    Finance & Insurance

    InfoSec Team
    • Comply with financial security regulations
    • Prevent AI leakage of customer financial data
    • Maintain auditable employee AI usage logs

    Public Sector

    Security Officer
    • Prevent AI leakage of government documents
    • Meet mandatory audit logging requirements
    • Control AI in air-gapped environments

    Enterprise & Manufacturing

    CISO / InfoSec
    • Block leakage of trade secrets and designs
    • Enterprise-wide AI usage visibility
    • Apply differentiated policies by department

    IT & Software

    Engineering / Security
    • Prevent code leakage via Copilot and Cursor
    • Approval and control of developer AI tools
    • Scope MCP integrations and agent tool access

    Healthcare & Bio

    Health Data Security
    • Prevent AI leakage of patient and clinical data
    • HIPAA and healthcare law compliance
    • Monitor and report clinician AI usage

    Agent-Adopting Enterprises

    AI Adoption Team
    • Detect Shadow AI and run approval workflows
    • Set and enforce enterprise AI policy
    • Know which internal systems agents reach, and with what scope

    Where we're going

    Next: MCP and AI Guardrails

    Not in the product yet — these are the problems we're taking on next.

    MCP Connection Visibility

    Nobody has an inventory of which agents reach which internal systems, or under what scope.

    Action Guardrails

    There is still no way to screen a tool call against policy in the moment before it runs.

    Indirect Prompt Injection

    Text planted in a document or ticket the agent reads still works as an instruction.

    Agent Action Audit

    With no record of what was called or what changed, there is nothing to trace after an incident.

    Enterprise-Grade Security

    Your data is safe with us

    Built with security and compliance at the core

    SOC 2 Type II
    GDPR Compliant
    ISO 27001
    HIPAA Ready
    99.99% Uptime
    Encrypted

    Security Features

    • End-to-end AES-256 encryption
    • Role-based access control (RBAC)
    • Multi-factor authentication (MFA)
    • Real-time threat detection
    • Automated security audits
    • Data residency compliance

    Protected Data Types

    Personal Identifiable Information (PII)

    SSN / ID NumbersPassport NumbersCredit Card NumbersBank AccountsEmailPhone Numbers

    Internal Identifiers

    Employee IDMilitary IDInternal ID

    Authentication & Security (Critical)

    PasswordsAPI KeysAccess TokensPrivate Keys

    Financial Information

    Purchase AmountSales RevenueSalary Info

    Medical & Health (PHI)

    Medical RecordsPrescription Info

    Legal & Contract Documents

    ContractsNDAMOU

    Sales & Strategy

    Price ListsCustomer ListsProposals

    Technology & IP

    Source CodeAPI SpecDB SchemaLogs / Errors

    Trade Secrets

    Manufacturing ProcessInternal Know-howPricing Logic

    Do You Know What You've Handed AI?

    In most organizations AI tools are already wired into internal systems, and security has no inventory of them. FlowGuard AI starts by building that inventory.

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