Pillar 02
Cloud Engineering & DevSecOps
Infrastructure built as code and delivered through pipelines with security gates, so what ships is what was reviewed.
What we build
Delivery you can move fast on and still defend.
We treat security as part of engineering, not a checkpoint at the end. Environments are reproducible, changes are reviewable, and every release carries the evidence of how it was made.
Cloud architecture and landing zones
Account structure, network design, and guardrails that make the secure path the default path.
Migration engineering
Planned moves from on-prem or legacy hosting into cloud environments, with rollback and cutover discipline.
Infrastructure as code
Terraform-managed environments that are reviewable, repeatable, and auditable by design.
CI/CD with security gates
Pipelines that scan, sign, and verify artifacts before they reach production, so a failing gate blocks a release.
Container and workload hardening
Baseline images, policy, and runtime controls for container and Kubernetes workloads.
Web platform engineering
Design, hosting, and operation of business-critical web properties with security discipline.
AI in our practice
AI accelerates the build. It never becomes the authority.
We use AI to move faster on architecture, code, and review. We do not let it sacrifice reliability, security, or quality. AI assists our engineers and our pipelines; deterministic tools and human judgment remain the source of truth and the record an assessor can follow.
Faster build and delivery
AI helps our engineers draft code, write tests, trace behavior, and summarize findings, shortening delivery without cutting corners.
Deterministic tools decide
SAST, DAST, dependency, IaC, and secret scanning are the gates and the evidence. AI triages and explains their output; it does not replace it.
Kept inside your boundary
For regulated work, AI runs against in-boundary or appropriately authorized services under no-retention terms. Sensitive data is not sent to public models.
Human in the loop
AI proposes; an engineer disposes. Nothing touching a security control merges or remediates on an AI suggestion alone.
Treated as untrusted input
Suggested code and dependencies pass the same review, license, and supply-chain checks as any other input, guarding against injected or hallucinated packages.
Auditable by design
Where AI contributes, its use is governed and recorded, and mapped to frameworks such as the NIST AI Risk Management Framework.
Building, migrating, or hardening a pipeline?
Tell us where you are and where you need to be. We will scope the engineering plainly.