Privacy-Preserving AI
Infrastructure for the Enterprise
Train AI models across sovereign regions with end-to-end AES-256 encryption, federated learning, and zero-trust architecture. Your data never leaves the device. From Dubai to Delaware.
Every layer of Aegis is engineered for zero-trust privacy. From the Rust crypto core to the compliance engine, security is not a feature — it is the foundation.
AES-256-GCM Encryption
Military-grade encryption powered by a pure-Rust crypto core. Every file encrypted at rest with streaming I/O — constant memory for multi-gigabyte datasets.
Federated Learning
Train AI models across distributed devices without centralizing data. Flower-based FL pipeline with crash-resilient checkpointing and secure aggregation.
Differential Privacy (DP-SGD)
Mathematically proven privacy guarantees. Rust-native Gaussian mechanism with L2 norm clipping adds calibrated noise to every model update.
Consent Management
GDPR Article 6 compliant consent engine with audit trails. Grant, revoke, and enforce data access policies with sub-second latency.
Cross-Platform SDK
Single Rust codebase, four platforms. UniFFI generates native Swift (iOS), Kotlin (Android), and Python bindings from one source of truth.
Compliance Engine
Built-in GDPR, HIPAA, UAE PDPL, and India DPDPA mapping. Automated audit logging, data minimization, and crypto-shredding for Right to Erasure.
From raw data to AI model
— without a single data leak
Encrypt & Store
Data is encrypted on-device using AES-256-GCM via the Rust crypto core. Files are stored with UUID-based physical names in a streaming vault — no raw data is ever exposed.
// Rust-native encryption
let vault = Vault::new(path, key)?;
let uuid = vault.store_file(
"patient_records.csv"
)?;
// File stored as: a3f7b2...enc
// Original name encrypted in headerTrain Locally
AI models train on-device using PyTorch. Data never leaves the user's control. Differential Privacy (DP-SGD) adds calibrated Gaussian noise to every gradient update.
# Federated training with DP
client = AegisClient(model, data)
update = client.fit(global_weights)
# Rust DP engine: clip + noise
privatized = engine.privatize_update(
update, sigma=1.0, clip=1.0
)Aggregate Securely
Only privatized model updates reach the server. Flower-based FL coordinator validates, aggregates via FedAvg, and distributes the improved global model. No individual data is reconstructable.
# Server sees ONLY aggregated updates
strategy = AegisPrivacyStrategy(
privacy_level="high",
min_clients=3
)
# NaN/Inf filtering + checkpointing
# Individual data: mathematically
# unrecoverableFrom Dubai to Delaware, London to Bangalore — Aegis meets the compliance requirements of every target market.
Dubai & UAE
Data physically never leaves UAE — on-device compute guarantees sovereign data residency.
- Smart Dubai cross-agency AI without data sharing
- DHA hospital network federated diagnostics
- DIFC cross-border financial risk models
- Islamic Finance Sharia-compliant analytics
United States
HIPAA-compliant federated learning with SOC 2 certification and NIST 800-207 Zero Trust alignment.
- Hospital network AI training (Kaiser, Mayo, VA)
- Cross-bank fraud detection without data sharing
- Defense contractor Zero Trust AI
- State privacy law consent automation (12+ states)
United Kingdom
Directly addresses the NHS Palantir data controversy with a privacy-first federated alternative.
- NHS Trust AI diagnostics across 65M patient records
- FCA-regulated privacy-preserving fintech
- UK AI Safety Institute alignment (DP verification)
- Post-Brexit cross-border data compliance
India
DPDPA 2023 Section 4 consent automation with RBI data localization compliance built-in.
- Ayushman Bharat hospital network TB/diabetes AI
- UPI fraud detection across 10B+ monthly transactions
- Aadhaar-linked analytics without biometric exposure
- Android-first deployment for 500M+ devices
Infrastructure that scales
with your privacy requirements
From pilot to production. Available in USD, AED, GBP, EUR, and INR.
Starter
For teams exploring private AI infrastructure
- Up to 5 FL clients
- AES-256-GCM encryption
- Basic consent management
- 3 sovereign regions
- Community support
- SOC 2 compliance docs
Professional
For growing AI operations with compliance needs
- Up to 50 FL clients
- End-to-end encryption + DP-SGD
- Full compliance engine (GDPR, HIPAA)
- 8 sovereign regions
- Priority support + SLA
- Admin dashboard
- Prometheus metrics + alerting
- Audit log export
Enterprise
For regulated industries and sovereign deployments
- Unlimited FL clients
- Full encryption + SecAgg + TEE
- All compliance (GDPR, HIPAA, UAE PDPL, DPDPA)
- 14+ sovereign regions
- Dedicated CSM + 24/7 support
- Custom admin dashboard
- mTLS + certificate management
- On-premise / air-gapped deployment
- Custom training pipelines
- SOC 2 + ISO 27001 audit support
Government pricing programs available for UAE, UK, US, and India agencies.
Ready to deploy privacy-preserving AI?
Schedule a 30-minute technical briefing with our engineering team. See Aegis running live with federated learning, differential privacy, and end-to-end encryption.
Trusted by healthcare, finance, and government organizations across 4 continents
Trusted by innovative teams worldwide
From healthcare to finance, engineering teams around the globe trust Aegis to protect their most sensitive data while accelerating AI innovation.
Dr. Sarah Chen
Chief Medical Information Officer, Pacific Health Network
Ahmed Al-Rashidi
VP of Data & AI, Emirates Financial Group
Priya Sharma
Principal Engineer, Vajra Cloud Services