Cloud Architecture & Migration
Designing and moving workloads to cloud-native, resilient architectures.
Architecture, automation and operations for cloud you can depend on — reliable, secure and cost-governed, under expert control.
We design, build and run cloud infrastructure as one accountable engagement — from architecture and migration to day-two operations, security and cost governance.
Engineering discipline applied to infrastructure.
Cloud done well is invisible: it scales, stays secure, and doesn't surprise you on cost. We bring architecture and operational rigour together so the platform underneath your software is dependable.
Designing and moving workloads to cloud-native, resilient architectures.
Provisioning that is repeatable, reviewable and governed.
Monitoring, SLOs and incident readiness for production systems.
Hardening, identity and controls built into the infrastructure.
Right-sizing and visibility that keep spend predictable.
Ongoing, accountable day-two operations.
Experienced engineers own the work and AI accelerates it — never the other way around. This five-phase model is how we apply the Braindoos AI Engineering Framework: AI participates in every phase, calibrated to the work; a human owns every decision; approval is always human and standards always override AI.
AI accelerates requirement analysis, research and impact assessment; engineers define, validate and approve the requirements and own the architecture. No unvalidated assumption reaches the build.
AI generates code and tests at speed against approved standards; engineers own the code, the reuse and security decisions, and the architecture. AI does the heavy lifting; the engineer owns the result.
AI pre-screens every change — AI-assisted or hand-written — against the same standards and checklists; experienced developers make the final review judgment. "The AI wrote it" is never a defense.
AI generates tests for both expected and failure paths alongside the code; engineers own coverage and test adequacy and add the manual testing that judgment requires.
AI assists release notes, monitoring and production analysis; engineers approve every release, accept residual risk and decide on every fix. Continuous human oversight, AI-accelerated.
A look at the problems we've solved and the results that followed.
A European enterprise software company’s platform gives each customer a private, per-account knowledge base built from documents they upload, which the platform’s AI can then answer questions against.
Read Case Study →WordPress does not, by default, give a theme a single place where a page’s template, styling and behavior are declared once and consumed everywhere they matter — left to the platform’s defaults, that structure tends to scatter into per-page conditionals or a page builder’s own configuration.
Read Case Study →A European enterprise software company runs a required CI validation sequence against its frontend application, including an automated dependency-security check as one of the required steps.
Read Case Study →Book a consultation with our senior engineers. We'll discuss your current state and map a practical path forward — no obligation, no generic pitch.
Tell us the problem you're trying to solve. You'll speak with experienced engineers who can assess it honestly and outline realistic options — whether or not we end up working together.