Software Engineering

The full software lifecycle, from product strategy to launch and later modernization. We work under eleven sub-services: Product Strategy & Advisory, Mobile App Development, Web & SaaS Development, Custom Software Development, MVP Development, App Modernization & Migration, Performance Optimization, IoT & Beacon Solutions, Software Architecture & System Design, Database Engineering & Optimization, System Integration & Central Platforms.

In our estimation model the typical timeline band for MVP development is 6–10 weeks. What drives the timeline most is a clear scope: at the start of the project we write down, together, the assumption the first release must validate and the smallest feature set needed for it. The Cost Drivers page explains how to read the bands.

SaaS gives a fast start, low upfront cost and automatic updates; in exchange you accept limits on data location and customization, and a long-term subscription. On-premise gives full control and data locality, with a higher upfront investment and operating load. A hybrid is also possible: the component that needs control (for example, personal data storage) runs on-premise and the rest as SaaS. KVKK (Turkish data protection law) and sector regulation, especially in finance and the public sector, often decide this.

Native (Swift / Kotlin): camera- and AR-heavy apps, complex animation, OS-specific features or the highest performance. React Native: one codebase for both platforms, fast iteration and reuse of the JavaScript / TypeScript ecosystem (including code shared with the web); it is our choice for cross-platform work. We make the choice with you at the start of the project, based on the requirements.

On the web, Core Web Vitals: LCP under 2.5 seconds, INP under 200 milliseconds, CLS under 0.1. On the backend, p95 response time, database lock contention and cache hit ratio. On the frontend, JavaScript bundle size, critical CSS and lazy loading of off-screen content. Method: take a baseline with Lighthouse and real-user monitoring, make the improvements, then measure again with the same metrics.