The technologies we build with, and when to use each

How we choose a stack

Most projects do not fail because someone picked Node.js instead of Python. They fail because the stack did not match the team that would maintain it, the integrations it had to survive, or the load it would really see. So we start with four questions, in this order:

1. Who maintains it after launch? If your team already knows PHP or JavaScript, a technically “better” language they cannot support is a liability. We write code your developers can read.
2. What does it have to talk to? Payment gateways, Tally, an EHR, OEM portals, WhatsApp, an AI model. The integrations, and the libraries that exist for them, often decide the language.
3. What is the workload shape? Many concurrent connections (chat, live dashboards) favour Node.js; data and machine-learning work favours Python; a classic database-backed business app is well served by Laravel; a small, fast system agent suits Go.
4. How long must it live? We prefer runtimes with long-term-support releases, pin versions, and plan upgrades on a calendar instead of in an emergency.

Backend choices at a glance

Code, workflow tool or off-the-shelf?

Not everything needs custom software. A rough rule we use with clients:

• Buy when a mature product already covers 80% of the workflow and the rest is configuration. A CRM for a ten-person sales team is usually a subscription, not a project; our custom CRM page explains where that changes.
• Use a workflow tool such as n8n when the job is moving data between systems that already have APIs, with a few AI steps in the middle. It is quicker to change and cheaper to run than bespoke code.
• Write code when the logic is your competitive edge, the volume is high, the data is sensitive, or the integrations are unusual. That is where SaaS, AI agents and custom backends earn their cost.

What our own products are built with

We run our own software in production, so the stacks on these pages are not theory. This is what each product actually uses, taken from its code:

Notice what is not in that table: we do not run Python, n8n or Kubernetes products of our own, so those pages describe what we build for clients and how, without borrowed credibility. When you ask us about a technology we have not shipped in production, we will say so.

Where we work

We deliver remotely, to teams across India and abroad. For regional detail see AI automation in Tamil Nadu, custom software in Coimbatore, Kochi, Bangalore or all of India.