Security
Securing data, privacy, identity, and the cloud platforms underneath, with the Sentinel and Enclave frameworks engineered into the substrate.
Securing Data and the AI Built on It
Security Engineering Practice
Sakura Sky's Security Practice exists to protect the data and AI workloads that drive modern operations. Our work begins with data: classification, lineage, access governance, encryption, and the runtime controls that keep sensitive information defensible as it moves through pipelines, models, and agentic workflows.
From that foundation, we secure the cloud platforms data lives on, the AI systems built from it, and the operational substrate regulators and supervisory authorities expect to verify. Our engineers wire security into code, configuration, and pipelines so it stays effective when systems change.
This is also where our Governance, Risk & Compliance service lives: compliance falls out the back of well-engineered security work, and where the regulatory frame drives the requirements, our productised Praxis solution carries the load.
Where We Engineer
Data-Centric Security Operations
Data Protection & Privacy Engineering
Data security is our core. We deliver end-to-end classification, lineage, and lifecycle management for sensitive and regulated data. Privacy-by-design controls aligned to GDPR and adjacent regimes, DLP, confidential computing for sensitive workloads, and policy enforcement that runs at the gateway, in the pipeline, and inside the database. For EU regulatory engineering across GDPR, the EU AI Act, the EU Data Act, and MiCA, the work hands off cleanly to our GRC service and our productised Praxis solution. For SOC 2, ISO 27001, and HIPAA attestation, we work with partners including Vanta.
AI & Agentic Security Governance
We secure the full lifecycle of AI and agentic systems, from model development to production deployment. Our Sentinel framework enforces access controls, data isolation, and prompt protection to safeguard model integrity and prevent misuse. We design zero-trust pipelines for AI operations and establish governance models for responsible AI adoption, including the scope-of-action charters and human-in-the-loop checkpoints that regulators expect to see.
Threat Detection & Intelligence
We build detection and response systems that unify telemetry, automate analysis, and shorten time to containment. We integrate Google SecOps for unified threat detection and AI-assisted triage, and TruffleHog for credential and secret-leak detection across code, configuration, and infrastructure. Our security partner ecosystem is expanding as the threat surface shifts, with custom detection logic, intelligence feed integration, and response playbooks tailored to each client’s environment.
Cloud Security Engineering (IaC)
We design and implement secure, cloud-native architectures using our Enclave framework. Our engineers apply identity and access management (IAM), workload isolation, VPC segmentation, and encryption to safeguard every layer of the stack. Security is embedded early through shift-left controls in CI/CD, ensuring resilience and compliance from the first line of code.
Differentiators
What Makes Our Security Practice Different
Sakura Sky’s Security Practice combines deep technical expertise, automation-first engineering, and a forward-looking focus on AI and data security. We help organisations build resilient, compliant, and intelligent systems that protect data, applications, and the people who depend on them.
Data security at the centre
We treat data security as the starting point of the practice, not a downstream concern. Classification, lineage, access governance, and encryption are designed in from the first architectural conversation. AI security, cloud security, and compliance work all anchor back to whether your data is genuinely defensible.
AI-aware security
We have a distinctive capability in securing generative and agentic AI systems. Models, prompts, pipelines, and tool inventories are protected against leakage, manipulation, and misuse. Our approach combines model governance, zero-trust principles, and continuous validation to keep AI operations both innovative and safe.
Zero-Trust identity
We move organisations from perimeter-based security to a Zero-Trust model where identity is the new perimeter. Using workload identity and OIDC, we ensure every agent, service, and user is cryptographically verified and authorised under least-privilege.
Shift-left engineering culture
We embed security at the code and pipeline level, integrating controls directly into development workflows. Secure-by-design principles applied early in the lifecycle let teams identify and remediate risks before deployment, reducing exposure and ensuring every build meets reliability and compliance standards.