I’m Andrei. At Codinental I am responsible for the technical foundation on which products are operated, extended, and reviewed. That includes backend architecture, cloud environments, interface contracts, deployment processes, and the operational data a team needs for decisions.

What a dependable platform has to provide

A platform starts with clear standards. Identity, permissions, secrets, logging, monitoring, and release procedures are specified so development, operations, and business stakeholders work from the same technical basis. Every environment has to be reproducible. Every change needs a traceable path through review, testing, and approval.

Interfaces with binding contracts

I design APIs as contractual boundaries between systems. Data models, error models, versioning, limits, pagination, and idempotent flows are settled before implementation. That leaves fewer implicit assumptions in the client and reduces escalation during integration.

In practice, we document the details early. What happens in partial failures. Which security defaults apply. Which logs matter for operations and audit. Which responsibility remains with the calling system.

Cloud and delivery as a controlled process

I set up Azure environments with infrastructure as code, role-based access models, separated network segments, and documented policies. CI/CD is a controlled delivery process. Builds, tests, artifacts, approvals, and rollbacks are traceable throughout the engagement.

Kubernetes, container platforms, or leaner Azure services are selected by load profile, operating model, and maintenance effort. The deciding factor is viability in operation, including cost control, recovery behavior, and clear responsibility during incidents.

Operations with usable signals

Observability is part of the architecture from the start. Logs, metrics, traces, alerts, and dashboards answer concrete operational questions. Which transaction is affected. Which dependency is slow. Which threshold triggers escalation. The aim is diagnosability before a defect turns into an organisational problem.

AI at Codinental

We use AI internally for prototyping, variant work, and recurring analysis tasks. When AI is planned as a product capability, I treat it like any other production system component, with data preparation, model selection, evaluation, deployment, monitoring, and clear access control.

Measurable quality, secure data integration, and bounded decision scope matter in particular. Document-heavy processes need logging, approval levels, and escalation logic so outputs remain usable in daily operation.

How it connects in our team

I provide backend contracts, platform standards, and operational mechanics. Halil builds web and mobile logic on top of that foundation, with careful handling of states and error cases. Bianca translates the logic into flows, components, and interaction rules. The result is a product where technical and business decisions fit together.

If an existing system needs modernisation or a new product needs a dependable foundation, we can discuss the right starting point.