Mode A — Project by project
Every brief starts at zero.
- New foundations every time
- Knowledge locked in one repo
- Cost scales linearly with work
- Nothing compounds
Engineering team · Istanbul
We build AI into real products — our own models, our own apps, and the infrastructure underneath them.
01 Positioning
Most software work starts from zero every time. Ours doesn’t.
Mode A — Project by project
Mode B — Reusable systems
Rebuilt every time Written once, reused
Eleven people. Flat. The founder is still in the repo.
Infrastructure, model pipelines and agent layers, reused across every build.
A team set up to start the next one without starting over.
02 What we do
The same people and the same infrastructure, pointed three ways.
01
Our own AI models, mobile apps and web products.
02
The manual loop, replaced by a system that runs itself.
03
Mobile, web, backend — engineered as systems, not deliverables.
03 How we build
What we build, what we refuse to outsource, and what we keep.
P01
Auth, data access, agent runtimes, deploy pipelines. Written once, carried forward.
P02
We build and fine-tune rather than routing everything through someone else’s service.
P03
Adapters shape a base model to a real requirement. Narrow, testable, cheap to iterate.
P04
Inference close to the user. Lower latency, lower cost, data that stays put.
P05
Tool calling, ReAct loops and MCP — agents that do work, with the failure modes written down.
P06
The output isn’t a repo. It’s a loop that makes the next build cheaper.
Request path & reuse loop
Scroll the diagram sideways
04 In development
An Android product with the agent layer built in — tool calling and a ReAct loop on a clean, testable architecture.
In active development — the screen shows a representative agent trace, not a shipped interface.
05 Selected work
One live platform, one product in development, one research track.
Live in production
A production portal coordinating employees, administrators and customers for a cleaning services company. An n8n-built AI agent supports the customer request flow, handling on the order of ten requests a day.

In development
Kotlin and Jetpack Compose on Clean Architecture and MVVM, with an internal agent layer using tool calling and ReAct. October 2026, free with enterprise licensing.

Research
An ongoing research track in vision-language models, evaluated doctor-in-the-loop.
Research only — not a released product. No medical validation, no regulatory approval, and no claim about accuracy.

06 Engineering stack
The layers a SkyEngineX system is assembled from.
Layer 01
Layer 02
Layer 03
Layer 04
Layer 05
Layer 06
07 Team & culture
Build young. Think long-term. Ship fast.
Student-founded and student-driven. That isn’t a caveat — it is why we move quickly and keep the structure flat.
Unit 01
Mobile and AI products. Turning a model into something you can hold.
Unit 02
R&D and systems engineering. The parts everything else stands on.
Unit 03
Design and social media. How the work looks and how it travels.
• Where we stand
08 Join the team
Not a CV drop. Tell us what you built and what you want to get good at.
09 Contact
hello@skyenginex.com SkyEngineX · İstanbul