Technologies
Thirteen technologies, one bar: senior engineers, production references, and a stack chosen for your product, not for our comfort.
What the stack covers
Four frontend frameworks, four backend platforms, five mobile stacks. The list is short on purpose: short enough to be senior in every entry on it.
Frontend engineering
React, Next.js, Vue and Angular, chosen per project, not by habit. We optimize for Core Web Vitals, accessibility and a codebase your team can extend after handover.
Backend engineering
APIs and services in Python, Node.js, Ruby on Rails and Java. Typed contracts, tests in CI and observability from the first deploy, because that is where production incidents are won.
Mobile development
Native Swift and Kotlin when the platform matters; React Native, Flutter or Kotlin Multiplatform when one codebase should serve both stores. We help you make that call with numbers.
AI integration
Every stack on this page is built with AI in mind: LLM features behind typed APIs, retrieval pipelines, evaluation harnesses and cost controls. AI-first means designed in, not bolted on.
How we choose a stack
We score candidates against your product: team skills, hiring market, ecosystem maturity, hosting cost and exit cost. You get the comparison in writing before the first commit.
Engineering standards
Code review on every change, CI/CD from week one, automated tests as part of done, and documentation that survives handover. The same bar across all thirteen technologies.
How a technology earns its place
Scan
We track releases, roadmaps and community health across the ecosystems we work in. Most new tools stop here; the criterion is production readiness, not hype.
Evaluate
Candidates get a structured trial on a real internal project: developer experience, performance, operating cost and long-term maintenance risk. Measured, not felt.
Pilot
The first client use runs with a tight scope and senior oversight. A technology reaches a client project only after it has survived one of our own.
Review
Every stack on this page is re-reviewed yearly. A technology that stops earning its place gets a documented migration path, not silent decay.
Who this page is for
CTOs choosing a stack
You need a technology decision you can defend before the board and the team. We give you a written comparison scored against your constraints, not our preferences.
Founders without a technical cofounder
Someone has to make the stack call and own it. We choose boring where boring wins, modern where it pays off, and explain both in plain language.
Teams on a legacy stack
Your Rails, Java or Angular still pays the bills. We modernize incrementally, and we tell you plainly when a rewrite is the wrong answer.
Product leaders adding AI
The roadmap says AI, but your stack was not built for it. We integrate LLM features into existing systems without rebuilding everything.
Go deeper
Each technology on its own page: what we build with it and where it wins.
Questions, answered
Why only thirteen technologies?
Because senior in a few beats familiar with everything. Every technology here has real client projects behind it and is re-reviewed yearly. When your product needs something outside this list, we say so and help you find the right partner.
Which stack will you recommend for our project?
The one that scores best against your constraints: team, hiring market, timeline, hosting budget and integration landscape. You get the comparison in writing before the first commit, so the decision is yours and documented.
Native or cross-platform for mobile?
It depends on measurable things: the platform features you need, the team you have, the budget and the time to both stores. Cross-platform wins more often than purists admit; native wins when hardware, performance or platform UX is the product. We show you the trade-off in numbers.
Can you work with our existing codebase?
Yes, that is most of our work. We start with an audit, put tests around what we touch, and improve incrementally. A rewrite is the last resort, and we will tell you honestly whether you actually need one.
Does AI-first mean you push AI into everything?
No. It means every architecture we design leaves room for AI features later: clean APIs, event streams, well-ordered data. Where an LLM feature earns its cost we build it; where it does not, we say so.
Not sure which stack fits your product?
Book a free 30-minute call with a senior engineer. You leave with a shortlist and the reasoning behind it, whether or not we build it.
Talk to an engineer