Backend technologies
Backends chosen for the next five years.
Language choice matters less than the architecture around it — but hiring pool and operational cost are real.
Backend choices are hard to reverse. We weight hiring availability, operational cost and library maturity for your specific domain far more heavily than benchmark performance, which is rarely the binding constraint.
What we use
And why we picked each one.
Node.js
JavaScript on the server.
WhyOne language across frontend and backend, which genuinely reduces context-switching on small teams. Excellent for I/O-heavy APIs.
NestJS
Structured, opinionated Node framework.
WhyGives Node projects the architecture they otherwise lack. Worth it above a handful of endpoints.
Python & FastAPI
Python with a modern async API framework.
WhyThe right call when data, ML or scientific libraries are involved. FastAPI's automatic OpenAPI docs are a real benefit.
Django
Batteries-included Python framework.
WhyThe admin interface alone saves weeks on internal tools and content-heavy applications.
Laravel
The dominant PHP framework.
WhyFast to build business applications in, deep Indian hiring pool, and runs on inexpensive shared hosting.
Java & Spring Boot
Enterprise JVM stack.
WhyWhere you need it — banking, large enterprise integration, existing JVM estate. Verbose, but extremely well understood.
.NET
Microsoft's cross-platform application framework.
WhyStrong choice if you're already committed to Microsoft licensing and Azure.
Go
Compiled language built for concurrent services.
WhyWhere throughput and low memory genuinely matter. Smaller hiring pool, so we recommend it deliberately rather than by default.
Comparison
Node vs Python vs Laravel
Including what to watch out for in each. There is no option without a downside.
| Option | Strengths | Watch out for |
|---|---|---|
| Node.js | Shared language with the frontend; excellent for real-time and I/O-heavy work. | CPU-bound work blocks the event loop; needs discipline on error handling. |
| Python | Unmatched for data and ML; highly readable; huge library ecosystem. | Slower for raw request throughput; packaging and environments need care. |
| Laravel | Fastest route to a business application; cheap hosting; deep hiring pool in India. | Easy to write N+1 queries; less suited to real-time or high concurrency. |
How we choose
Four criteria, in this order.
Fit
Does it solve your actual problem, or a more interesting one?
Hiring pool
Could you hire for it in India if you took the project in-house?
Total cost
Licences, hosting and the operational time to run it — not just build cost.
Exit risk
How hard would it be to leave? We don't build things you can't walk away from.
Services
What we build with it.
- 01API DevelopmentVersioned, documented APIs your partners can build on.
- 02Custom Software DevelopmentSoftware built for how your business actually works.
- 03Web Application DevelopmentComplex, data-heavy applications that stay fast at scale.
- 04SaaS DevelopmentMulti-tenant products with billing and onboarding built in.
Almost never the question that matters. Your bottleneck will be database queries and third-party calls, not language throughput. Choose on hiring pool, library fit for your domain, and operational cost.
Yes. We regularly extend existing systems rather than replacing them — a rewrite is the most expensive option and rarely the right first move.
Only when the team size justifies them. Most businesses are better served by a well-structured monolith; microservices trade code complexity for operational complexity, and the second is harder.