Custom software and product development.

An MVP is the first version, with a fixed scope, a fixed price and a launch in 2 to 6 weeks. Custom software development is everything after that, or instead of it when a product already exists, with releases planned and shipped one after another for as long as the product needs a team. Most clients start with the first and continue with the second.

Yes. We build custom software for startups and for established companies, covering new products, internal tools, and the modernization of software that already runs the business. The process is the same, sized to the organization, with discovery, a prototype before code, and releases tested before they ship.

Yes, and it is a common way to start. We begin with a focused review of the code, the infrastructure and the product itself, tells you plainly what holds up and what does not, and plans the shortest route to the next release. A rewrite is the last resort rather than the first suggestion.

We release as often as the product and your users can absorb. Every change goes through automated tests and CI, and the risky ones through a second engineer, so releasing is routine, and on mobile the changes that do not need a store review go out over the air. We agree the rhythm with you and adjust it release by release.

You do, with one of our product leads making sure the decision is an informed one, grounded in what users are doing, what the last release changed and what each option costs. AI helps draft the specifications and size the work, and the priorities remain yours.

The same way on every release. Automated tests and CI run before anything ships, a second engineer reviews the changes that carry risk, and monitoring and error tracking surface problems before users report them. We build in the stack the product will grow in, so growth does not mean a rewrite.

Most often we work in the TypeScript ecosystem end to end, with React on the web, React Native with Expo on mobile, Node.js behind them, PostgreSQL first, with MongoDB, Neo4j or Redis when the data has a different shape, and AWS first, Cloudflare where it fits, and a plain server when that is the right size. For AI features, we use Claude, GPT, Gemini or open models, chosen per use case. We choose the stack for each product, and build in the one it will grow in.

Usually as time and materials billed monthly, with a team on the product for as long as it needs one and the scope adjusted release by release. A retainer suits products that need steady care rather than a full team, and a fixed price suits a scoped feature. When a product needs a lead more than it needs more hands, one of our leads takes the fractional CTO or CPO seat.

Yes. We set up and run the infrastructure the product needs, with AWS first, Cloudflare where it fits, or a plain server when that is the right size, along with Docker-based deployments, separate development, staging and production environments, CI/CD on every change, and monitoring and error tracking from the first release. When a product outgrows where it started, we migrate it.

Yes. AI features are built into the product with the same discipline as any other feature. They are prototyped against your real data, measured with an evaluation set before they ship, and monitored afterwards. We work with Claude, GPT, Gemini and open models, chosen per use case, and your data stays in your own accounts.