Custom software and product development

An MVP is the first version: a fixed scope, a fixed price, live in 2 to 6 weeks. Custom software development is everything after that, or instead of it when a product already exists: 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, and WeaveLines runs both with the same people.

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

Yes, and it is a common way to start. WeaveLines begins with a short 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, not the first suggestion.

As often as the product and your users can absorb. Every change goes through review, automated tests and CI, so releasing is routine, and on mobile the changes that do not need a store review go out over the air. WeaveLines agrees the rhythm with you and adjusts it release by release.

You do, with a product lead from WeaveLines making sure the decision is an informed one: what users are doing, what the last release changed, what each option costs. AI helps draft the specs and size the work; the priorities stay yours.

The same way on every release: a second engineer reviews every change, automated tests and CI run before anything ships, and monitoring and error tracking tell us about problems before users do. WeaveLines builds in the stack the product will grow in, so growth does not mean a rewrite.

The TypeScript ecosystem end to end: 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, Claude, GPT, Gemini or open models, chosen per use case. WeaveLines chooses the stack for each product and builds in the one the product will grow in.

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

Yes. WeaveLines sets up and runs the infrastructure the product needs: AWS first, Cloudflare where it fits, or a plain server when that is the right size, 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 like any other feature: prototyped against your real data, measured with an evaluation set before they ship, and monitored after. WeaveLines works with Claude, GPT, Gemini and open models, chosen per use case, and your data stays in your own accounts.