Aego
The Multi-Layered Security Fortress for Data Assets
Constructing an impenetrable defense perimeter for the AI supply chain. From storage to computation, we employ privacy-preserving technologies and adversarial defense to ensure data remains sovereign, uncorrupted, and confidential in an open ecosystem.
Why Aego Exists
Aego exists to immunize the AI data lifecycle against emerging adversarial threats and privacy breaches.
Traditional security fails in the AI era.
Firewalls and perimeter defenses cannot stop prompt injection, jailbreaks, or inference-time exploits, while sensitive data remains exposed during training and computation.
[ The perimeter is secure, the data is not. ]
Data poisoning corrupts model integrity.
Malicious triggers and poisoned samples are covertly embedded in training datasets, causing models to learn hidden behaviors and activate sleeping backdoors under specific conditions.
[ Data is ingested, but trust is compromised. ]
Model inversion leaks private assets.
Attackers reverse-engineer training data from model outputs, reconstructing sensitive PII, proprietary content, or confidential records that were never meant to be revealed.
[ Value is delivered, but secrets are stolen. ]
Core Capabilities of Juro
Privacy-Preserving Computation
Enable model training on encrypted data using MPC and TEE without decryption.
Adversarial Defense Matrix
Detect and sanitize poison attacks, backdoor triggers, and adversarial samples.
LLM Firewall
Real-time filtering of prompt injections and jailbreak attempts during inference.
Differential Privacy Shield
Add statistical noise to outputs to prevent memorization and re-identification.
Data Sovereignty Control
Granular access policies ensuring data never leaves approved geo-fences or enclaves.
Continuous Red Teaming
Automated AI agents constantly attack your assets to identify zero-day vulnerabilities.
Schematic Blueprint
CORE
AEGO
SYSTEM SECUREData Asset Types Supported by Juro
Sensitive PII & Healthcare Data
Encrypted storage and computation for medical records, financial logs, and biometric IDs.
High-Value Intellectual Property
Protection for proprietary algorithms, trade secrets, and industrial blueprints.
Vector Embeddings
Securing vector databases against reconstruction attacks and unauthorized similarity search.
Model Weights & Parameters
Preventing model extraction/stealing via API hardening and weight encryption.
Fine-Tuning Datasets
Ensuring clean, poison-free instruction sets for RLHF and SFT processes.
Prompt Libraries & Context
Shielding system prompts and long-context windows from leakage via prompt injection.