Enterprise Privacy Platform

The AWS of Privacy

Data without limits. Analytics, AI and sharing with zero regulatory risk.

SOC 2 Type II GDPR HIPAA CCPA
<0.3%
Re-identification Risk
12ms
Avg. Latency
99.9%
Uptime SLA
ε < 1
Differential Privacy

Privacy Firewall for Enterprise Data

Connect any data source. Apply differential privacy. Share with confidence.

Data Ingestion

Connect to databases, data warehouses, lakes, and APIs. Support for SQL, NoSQL, Snowflake, BigQuery, S3, and more.

  • 50+ native connectors
  • Encryption in transit & rest
  • OAuth & SAML authentication

Privacy Engine

Apply mathematically-proven differential privacy algorithms with visual privacy budget management.

  • Gaussian/Laplacian noise
  • Synthetic data generation
  • PATE for ML training

Secure Output

Generate differentially private outputs in any format with complete audit trails and compliance reporting.

  • CSV, JSON, API endpoints
  • Role-based access control
  • Immutable audit logs

How It Works

1

Connect

Link your data sources securely

2

Configure

Set privacy parameters (ε)

3

Transform

Apply DP algorithms

4

Share

Export compliant data

Built for Regulated Industries

Trusted by organizations that handle the world's most sensitive data.

Healthcare

Analyze patient data for research and AI training while maintaining HIPAA compliance.

LifeLabs WELL Health Cleveland Clinic

Finance

Fraud detection, risk modeling, and customer insights with regulatory confidence.

Alterna Savings Meridian Desjardins

Government

Cross-agency data sharing for policy insights while protecting citizen privacy.

Public Health Smart Cities Census Bureau

Technology

Train AI models on proprietary data without privacy risks or data silos.

AI Startups Data Science ML Platforms

Pharmaceuticals

Secure drug development and clinical trial analysis across entities.

Clinical Trials Biotech Research Labs

Telecommunications

Usage analytics and predictive maintenance for millions of users.

Telco Providers IoT Networks 5G Operators

Unlock Data Value. Protect Privacy.

Enable use cases that were previously impossible due to privacy constraints.

Data Sharing & Collaboration

Share sensitive data externally with researchers, partners, and government agencies without risking individual privacy. Enable internal collaboration across departments without granting direct access to raw data.

Share data with 100% privacy guarantees

Regulatory Compliance

Meet GDPR, CCPA, HIPAA, and other privacy laws with mathematically-proven differential privacy. Generate compliance reports and audit trails automatically.

Reduce compliance risk by 95%

Privacy-Preserving AI/ML

Train machine learning models on sensitive data while maintaining differential privacy. Use PATE and synthetic data generation for responsible AI development.

Train models without privacy risks

Data Monetization

Monetize data assets and create data-driven products while respecting privacy. Build customer trust through demonstrated commitment to data protection.

Create new revenue streams

Connect Your Entire Data Stack

50+ native integrations. APIs for everything else.

Databases

  • PostgreSQL
  • MySQL
  • MongoDB
  • SQL Server
  • Oracle

Data Warehouses

  • Snowflake
  • BigQuery
  • Redshift
  • Databricks
  • Azure Synapse

Cloud Storage

  • AWS S3
  • Azure Blob
  • GCS
  • Data Lake
  • Delta Lake

BI Tools

  • Tableau
  • Power BI
  • Looker
  • Metabase
  • Mode

REST API

# Apply differential privacy to a dataset
curl -X POST https://api.cloud9security.ai/v1/privacy/apply \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "source": "snowflake://prod-db",
    "table": "customer_data",
    "epsilon": 0.1,
    "algorithm": "gaussian_noise",
    "columns": ["age", "income", "spend"]
  }'

See Cloud9 in Action

Schedule a personalized demo with our team. We'll show you how Cloud9 can unlock your data while ensuring compliance.

  • Live platform walkthrough
  • Custom use case analysis
  • ROI calculation
  • Security review

Demo is simulated. No real data is processed.