A full-stack software partner with global reach.
Based in Vadodara, India and run by senior engineers — a primary development partner and NDA-backed white-label team for agencies. Small enough to care, deep enough to deliver.
Started small. Stayed sharp.
Keyntech is a full-stack software development company with 10+ years of experience building scalable, secure, tailored software. We've delivered 100+ projects for agencies, startups and enterprises worldwide.
We work two ways: as a primary development partner, and as a discreet, NDA-backed white-label team for agencies — where your clients only ever see you. Trusted by teams across the US, Australia, Switzerland, Israel and Singapore.
Our work spans PHP (Laravel, CodeIgniter, Slim), Node.js, React and Angular, plus WordPress, Shopify and HubSpot — combined with practical, production-grade AI. We treat the boring problems as carefully as the new ones.
Make excellent software engineering accessible to teams who care about how it's built.
Be the long-term engineering partner founders introduce to their next company.
The five things we won't compromise.
Quality engineering
Clean, documented, maintainable code with senior-level architecture. Tests where they earn their keep, docs that survive the author leaving.
Transparency
Real access to repos, sprint boards and decisions. No black boxes, no theatrical status updates.
Ownership
We treat your codebase like it has our name on it — even when, under white-label, it doesn't.
Applied AI
We use AI where it makes the work better and measure whether it did — across Claude, OpenAI, Gemini and DeepSeek.
Discretion
NDA-backed white-label delivery. When we work behind your brand, your clients only ever see you.
AI + human engineering.
We don't ship AI for spectacle. We use it where it makes the work better, and we measure whether it did.
AI does the boring parts.
Boilerplate, tests, scaffolding, migrations and code-review pre-passes — done by copilots, validated by engineers.
Humans do the judgement.
Architecture, contracts, edge cases, and the question of whether we should build the thing at all.
Evals are a discipline.
We measure AI output the way we measure code: with tests, telemetry and clear acceptance criteria.
Code is still the artifact.
AI accelerates writing it. It doesn't replace understanding it. Every line ships clean and documented.