AI Adoption Without Guidelines
Generative AI tools are being adopted rapidly in the field, but there's no governance framework to defend against sensitive data leaks and prompt injection.
Enterprise AI Security & GovernanceGenerative AI,
Generative AI,
the safe way to use it
By connecting detection → monitoring → feedback loop into a single security full-stack, we block sensitive data leaks and threats in real time and continuously enhance detection quality.
AI Security Workspace
PII Detection
Labeling Loop
Challenge"We used AI,
"We used AI,
but no one knows what was entered"
Generative AI tools like ChatGPT and Claude are rapidly penetrating the field, but there's no way to track what was entered. Adopting AI without proactive defenses against sensitive data leaks, prompt injection, and model drift is like storing valuables with the door left open.
Lack of Threat Visibility
You can't track who entered what data into AI and when, making post-hoc audits impossible and accumulating compliance risk.
Stagnant Detection Quality
Even when policies are updated, the detection model stays the same, so false positives and false negatives repeat and response quality doesn't improve over time.
ArchitectureFrom detection to learning,
STAGE 1 STAGE 2 STAGE 3 STAGE 4
From detection to learning,
an unbroken security loop
It doesn't stop at simple blocking. Four stages — PII detection → threat monitoring → labeling feedback → policy engine — are organically connected so security quality automatically rises as you operate.
PII Detection
Scans prompts and attachments in real time to classify personal and confidential data and blocks it instantly before transmission.
Threat Monitor
Integrates monitoring of risk ratios, blocking events, and attack types by organization in a single dashboard to immediately identify anomalies.
Labeling System
When security staff label false positives and true positives, the results are automatically fed back into the detection policy's training data, continuously improving quality.
Policy Engine
Manages differentiated security policies at the organization, business unit, and user levels, and applies policy changes to the detection pipeline with zero downtime.
Security Operations Layer
Zero-downtime Deploy
Applies policy changes to the detection pipeline instantly with no service interruption.
Audit Log & Incident Report
Retains all detection and blocking events as logs to support compliance audits.
Drift Detection
Periodically detects changes in model behavior to alert on unexpected quality degradation in advance.
Key Features
AI Security as an Operational System
It's not security that ends with a single block. True security requires a structure where detection quality is learned, policies are automated, and operators can grasp everything at a glance.
Real-Time PII & Confidential Detection
Combines rule-based patterns with context analysis to block resident registration numbers, card numbers, and internal strategy documents before prompt transmission.
Integrated Threat Monitoring Dashboard
View blocking counts by organization, risk type distribution, and time-series events at a glance so security operators can act immediately.
Feedback Loop-Based Quality Enhancement
Feeds labeling results back as training data to continuously improve the detection model and increase adaptability to new threat types.
Granular Policy Governance
Sets differentiated security policies by organization, department, and role, and automates policy version history and change-approval flows to maintain compliance.
Impact MetricsReal-Time 3-Layer Automated Continuous
We Prove Security Operations with Numbers
The real metric for AI security isn't how much you blocked, but how accurately you detect and how quickly you improve.
PII Detection
Instant detection and blocking of sensitive data before prompt/file transmission
Defense
3-step security full-stack: detection → monitoring → feedback loop
Policy Sync
Zero-downtime application of policy changes to the detection pipeline
Self-Improving
Continuous detection quality enhancement via labeling feedback
Technology StackFrom detection to compliance,
From detection to compliance,
an enterprise AI security full-stack
Detection Layer
Rule-based Pattern MatchingContext-aware NLPFile Content ScannerPrompt Inspector
Monitoring
Threat DashboardRisk ScoringEvent TimelineOrg-level Analytics
Feedback & Learning
Labeling UIFalse Positive FeedbackPolicy Learning LoopAuto Retraining
Policy Governance
Role-based PolicyDepartment SegmentationVersion ControlApproval Workflow
Operational Stability
Zero-downtime DeployAudit LogAlert SystemRollback Support
Compliance
DLPDrift DetectionAccess ControlIncident Report
Adopt Generative AI
Safely with Governance
You can immediately evaluate an enterprise AI security full-stack that includes PII detection, threat monitoring, a feedback loop, and policy governance.