Software development, built in India for US teams

The kind of software we build

Most of our work falls into a handful of shapes. The first is web applications: the dashboards, portals, and customer-facing products that a business actually runs on. The second is APIs and backend services, the parts nobody sees but everything depends on, where getting the data model and the contracts right matters more than the interface.

We also build a lot of internal tools. These rarely get a launch announcement, but a good ops console or admin panel can save a team hours every day and quietly pay for itself. And increasingly we build AI-enabled products, where a language model, a retrieval pipeline, or an agent sits inside the application and does work that used to be manual.

We treat AI as a feature of the software, not the point of it. If a problem is better solved by a clear schema and a few well-named functions, that is what you get. We reach for a model when it genuinely does something a deterministic system cannot.

How we work

We start with scoping. Before anyone writes code, we want to understand what you are trying to do, who it is for, and what the first useful version looks like. Often that conversation shrinks the project, which is usually good news for your budget.

Then we build in the open. You get access to the repository, a running preview environment, and regular check-ins where you can see real software instead of a slide. We ship in small slices so you can react early, while changes are still cheap, rather than at the end when they are not.

After launch we stick around. Software needs maintenance, the first users always surface things you did not predict, and the roadmap keeps moving. We can stay on as the team that keeps the product healthy, or hand off cleanly to your own engineers with documentation they can actually follow.

The stack we favor and why

We default to TypeScript across the front and back end, usually with React and Next.js on the client and Node or Python on the server. A single language across the stack means fewer context switches, shared types, and engineers who can move between layers without friction. For data we lean on PostgreSQL, because boring and reliable is a feature.

On the AI side we work with the major model providers and the tooling around them, including retrieval, evaluation, and agent frameworks. We are deliberate about which model goes where, since the cheapest model that clears the bar is often the right one.

None of this is dogma. The point of a default stack is that we are fast and confident in it, not that we force it onto every project. If you already run on a particular framework or cloud, we work in your world rather than asking you to rebuild for ours.

Why FoundrySoft

Working with a team in India usually raises the same worries: communication, time zones, and quality. We have built the studio to answer all three. We keep a real overlap with US hours, so you are not waiting a day for an answer to a one-line question. The people on your project are senior engineers who can make decisions, not a rotating cast of juniors learning on your budget.

You own everything we make. The code lives in your repositories, the IP is yours in full, and there is no contract clause that holds your own product hostage. We would rather earn the next phase than trap you in this one.

And we move in weeks, not months. A small senior team with a clear scope and a short feedback loop simply gets more done than a large one with a long one. That is the whole pitch: serious software, owned by you, shipped sooner than you expect.

Common questions