Security & Secure AI Framework (SAIF)
How Quinovaz operationalizes enterprise-grade cyber defense and aligns with the Google Secure AI Framework (SAIF) to build trustworthy, robust, and sovereign AI solutions.
Zero Data Leakage to Public LLMs
Client data and enterprise queries are never utilized to train or fine-tune public foundational models. Complete sovereign isolation.
End-to-End Cryptography
Rigorous AES-256 data at rest encryption, TLS 1.3 in-flight tunnels, and hardware security module (HSM) managed keys.
Zero-Trust Architecture
Continuous verification, least-privilege role boundaries, and container sandbox isolation for every service deployment.
The 6 Pillars of the Secure AI Framework (SAIF)
Quinovaz integrates these six pillars directly into all engineering sprints, AI copilot builds, and DataLE Labs analytics platforms:
Expand Strong Security Foundations to the AI Ecosystem
We secure the entire AI development and runtime lifecycle. All microservices, vector databases, and model weights reside in isolated, VPC-peered network perimeters with strict cryptographic secrets rotation.
Extend Detection & Response into AI Threat Profiles
Our architectures incorporate runtime telemetry to detect prompt injection attacks, model hallucinations, adversarial perturbation, and data exfiltration attempts in real time.
Automate Defenses Against Evolving Attack Vectors
Automated CI/CD security gating, static and dynamic analysis (SAST/DAST), and dependency vulnerability scans ensure patches are applied before code reaches staging or production.
Harmonize Platform-Level Controls Across Teams
Uniform identity and access management (IAM), role-based permissions (RBAC), and immutable audit logs guarantee consistent governance across both cloud infrastructure and AI pipelines.
Adapt Controls with Continuous Feedback Loops
We implement human-in-the-loop (HITL) checkpoints and real-time safety guardrails, enabling rapid tuning of model safety boundaries without causing service downtime.
Contextualize AI Risks Within Business Workflows
AI risks are evaluated directly against your compliance frameworks and business objectives, ensuring verifiable data provenance, explainability, and regulatory conformity.
Reporting Security Inquiries & Vulnerabilities
We welcome responsible disclosure from security researchers, auditors, and enterprise clients. If you discover a potential vulnerability or have questions about our cryptographic implementations, please notify our security engineering team immediately.