The Technology We Build With, Across Every Engagement
From agentic AI systems built on Claude and modern LLM tooling to enterprise Java services, SaaS platforms, mobile apps, and industrial edge software - we bring a broad, production-proven stack to whatever industry we're working in, not a narrow specialty we try to force onto every problem.
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Core Disciplines
Every category on this page reflects work we actively do for clients today - agentic AI systems built with Claude and other frontier models, enterprise Java and SaaS platforms, modern web and mobile apps, cloud infrastructure, and industrial edge software. Several of these disciplines are also proven inside our own products, upmarX and Skelbiz, but our engineering practice is built to serve any industry, not just ed-tech and manufacturing.
We standardize where it earns its keep and specialize where a client's domain demands it. A focused core toolset means faster onboarding for new engineers and infrastructure patterns we've already hardened through real production incidents; the flexibility to bring in Java, Python, or a client's existing stack means we adapt to your environment instead of asking you to adapt to ours.
What We Build With
Six disciplines we actively work in, spanning agentic AI through to industrial edge software.
AI & Agentic Development
Enterprise & SaaS
Frontend & Web
Mobile
Cloud, Data & DevOps
Edge & IoT
Chosen for Production, Not for Novelty
Every choice below was made for a reason we can point to in a running system, our own or a client's.
- Claude and modern LLM tooling power the agentic AI systems we build for clients, chosen for reliability and strong reasoning over raw novelty
- Java and Spring Boot give us a proven foundation for enterprise-grade services where stability and long-term maintainability matter most
- TypeScript end-to-end reduces integration bugs across frontend and backend by catching type mismatches before deployment
- Multi-tenant SaaS architecture patterns let us stand up new client platforms without re-solving the same infrastructure problem each time
- Rust powers our edge agents where reliability under poor connectivity matters more than raw development speed
- AWS and Kubernetes let us scale client infrastructure without re-platforming when usage moves beyond the original estimate
How We Evaluate New Technology
We're deliberately conservative about adding new tools to the stack - here's the bar something has to clear first.
Prove It Internally
New tools get tested inside upmarX or Skelbiz first, under real production load, before we recommend them to a client.
Weigh Maintenance Cost
We favor boring, well-documented technology over novelty - a stack our team can support in three years, not just today.
Match the Client's Reality
When a client already runs on a different stack, we adapt rather than force a migration that isn't the actual goal.
Document the Decision
Architecture choices are written down and reviewed with you, so the reasoning outlives any single engineer's memory.
See the Stack in Action
Building on a Different Stack?
We adapt to your existing infrastructure when migration isn't the goal.
Discuss Your Project