01
Isolated landing zones
Each engagement runs in its own account or subscription boundary with policy guardrails, budget controls and no lateral network path to any other environment.
Secure by architecture, not by promise.
Every environment we build or operate follows a service-secured model: security controls are part of the architecture itself — provisioned as code, enforced at the network layer, and verifiable in the audit log — rather than bolted on afterwards.
We build where you already trust your workloads.
We design and operate AI workloads across AWS, Microsoft Azure and Google Cloud, as well as hybrid estates that bridge cloud and on-premises systems. Client workloads run in isolated landing zones — dedicated, policy-enforced environments within your own tenancy or a segregated account structure — so no client's data, keys or compute is ever shared with another's.
02
High availability by design
Multi-availability-zone deployment as standard, with defined recovery objectives, automated failover for critical services, and tested restore procedures — not just backups.
03
Infrastructure as code
Environments are provisioned from version-controlled templates. Every change is reviewed, every deployment is reproducible, and drift is detected automatically.
04
Zero-trust network isolation
No implicit trust between services. Private networking by default, identity-based access to every workload, and explicit allow-lists instead of open segments.
05
Encryption everywhere
Data encrypted at rest with AES-256 and in transit with TLS 1.2+. Keys are held in managed KMS/HSM services, rotated on schedule, and never leave your control boundary.
06
Hardened AI endpoints
Model access is brokered through authenticated, rate-limited gateways with content controls — never raw keys handed to applications or individuals.
Monitored continuously. Rehearsed regularly.
Continuous monitoring & logging
Centralised, tamper-evident logging across infrastructure, applications and model calls, with automated alerting on anomalous access, configuration change and unusual data movement. Logs are retained to the schedule agreed in each engagement's data processing terms.
Incident response
A documented incident-response process with defined severities, escalation paths and client notification commitments — including notification without undue delay where personal data may be affected, in line with UK/EU GDPR obligations.
Vulnerability management
Dependency and image scanning in every build pipeline, scheduled patching windows, and prompt-injection and abuse testing for AI-facing surfaces as part of our evaluation practice.
Aligned to recognised standards
Our controls are designed around ISO/IEC 27001 principles, the NCSC Cloud Security Principles and the shared-responsibility models of AWS, Azure and GCP. Where clients hold their own certifications, we operate inside their control frameworks.
Private networking by default
AES-256 at rest · TLS 1.2+ in transit
Managed KMS / HSM key custody
Multi-AZ resilience & tested recovery
This page describes the operating framework of Genius AI Solutions Ltd and is provided for information. It is not legal advice, and it does not amend any contract. Engagement-specific terms — including data processing agreements — are agreed in writing before work begins.
Security questions? Ask them.
We're happy to walk your security team through our architecture, controls and evidence — before any contract is signed.