Custom Software Development
The systems your AI runs on, engineered to scale.
AI is only as good as the platform underneath it. We build the backends, pipelines and products that stay fast when traffic multiplies, because we've been the ones paged when they don't.
What we build
Scalable backends & APIs
Services designed around queues, idempotency and horizontal scale, so spikes buffer instead of cascading into outages.
Data & ML pipelines
Streaming and batch pipelines that are replayable, observable and cheap to operate. This is the substrate every serious AI initiative sits on.
Full-stack products
Web applications from database to pixel: Next.js and React frontends, typed APIs, auth, billing and admin, shipped as one coherent system.
Modernization & rescue
Strangler-pattern migrations that replace fragile systems incrementally, with shadow traffic proving parity before anything is cut over.
How we keep systems fast as they grow
Architecture for the second year
The expensive failures happen after launch, when growth finds the shortcuts. We design for the load you'll have, not the load you have, without gold-plating you don't need yet.
Observability first
Metrics, tracing and cost attribution go in before features. You can't fix, or bill for, what you can't see.
Boring technology, deliberately
Postgres before exotic databases, queues before microservice sprawl, proven infrastructure before the new hotness. The innovation budget is spent where it differentiates you.
AI-ready by default
Clean data models, event streams and typed APIs mean that when you add AI later, the integration takes weeks, not quarters. Most of our software clients become AI clients.
Typical engagements
- MVP to production: taking a validated prototype to real scale
- High-throughput data platforms for analytics and ML
- SaaS product engineering, end to end
- Legacy system modernization without a big-bang rewrite
- Performance rescue: finding and fixing the latency curve
FAQ
Questions we hear a lot
What technologies do you specialize in?
TypeScript and Node.js plus Python on the backend, Next.js and React on the frontend, PostgreSQL as the default database, Redis and Kafka for caching and streaming, Docker and Kubernetes on AWS, GCP or Azure. We choose deliberately per project, and we'll explain every choice in writing.
Why hire developers in India through Mindela?
Senior engineering at India economics. US agencies bill 150 to 300 dollars an hour; experienced Indian teams deliver equivalent quality at a fraction of that. The difference with us is the bar: our engineers have worked on frontier-lab projects, and every engagement is senior-led with evals, reviews and documentation as standard.
How do you handle project pricing and timelines?
Fixed price for well-defined scopes, sprint-based for evolving products. Either way you get working software every week and a live view of progress, not a big reveal at the deadline.
Can you take over an existing codebase?
Yes. We start with a paid audit covering architecture, tests, security and the deploy pipeline, so both sides know what we're inheriting. Then we stabilize before we extend. We won't quote blind on someone else's code, and you should be suspicious of anyone who will.
What about maintenance after launch?
Every build includes documentation, runbooks and handover. If you want us to keep operating it, we offer retainers with defined response times, monitoring and a monthly improvement budget.
Ready when you are.
Tell us what you're working on. You'll get an honest read on feasibility, timeline and cost.