The backend is where products quietly succeed or fail. We build Node.js APIs with PostgreSQL that handle payments, integrations and real-time updates correctly, then hand you the code and the accounts.
Node.js lets developers run JavaScript on the server. It is open source and has been a standard choice for web backends for many years. Its strength is handling a large number of small requests at once: API calls, chat messages, notifications, webhooks from payment providers. That describes the daily work of most business software, which is why Node sits behind so many web and mobile products.
Choose Node.js when your product is an API serving a web or mobile app, when it must talk to many outside services, or when it needs live updates. It is especially practical when your front end is already React or React Native, because one language runs across the whole product and engineers can move between layers. Node is a weaker choice for heavy number crunching, such as video processing or training models. That work belongs in a different tool, called from Node.
Documented APIs for web and mobile clients, with versioning so an app update never breaks older installs.
Stripe payments, subscriptions, refunds by rule and payouts, with reconciliation between prepaid and cash orders.
Connections to point of sale, accounting, inventory, CRM and shipping systems, tested with mock orders before launch.
Chat, live order status and notifications delivered over persistent connections.
Queues and scheduled tasks for emails, reports, imports and anything that should not make a user wait.
Backends that call AI models, manage prompts and keys safely on the server, and control usage cost.
We design the PostgreSQL schema and the API contract before writing handlers. Most backend problems are data model problems discovered too late.
A staging API with documentation goes live early, so front end work and your own review can start against real endpoints.
Payments, refunds, roles and outside systems are built in milestones. Every integration is exercised with mock orders and checked field by field.
Logging, error alerts, backups and rate limits are set up before launch. You receive the repository and a 14-day bug-fix window.
Node handles many requests by never waiting around. One slow calculation placed in the wrong spot makes every user wait. Heavy work must go to a queue or a separate worker.
An integration that works with one sample order can fail on bulk imports, odd characters or a changed field format. We learned to run mock orders through every connected system before launch.
It is easy to install a package for every small task. Each one is code you did not write and must keep updated. Fewer, well-maintained dependencies mean fewer security notices later.
Payments break quietly when nobody defined what happens on cancellation. A written matrix of who gets what back, and when, must exist before the payment code does.
Use Node.js when the product is mainly an API with many integrations and live updates, and when your front end is JavaScript. Use Python when the core of the product is data analysis or machine learning. Many products use both: Node for the main API and a small Python service for the data work.
A backend is normally priced as part of a product. Our MVPs start from $10,000 including source code and deployment, and take about 7 days when well scoped. Cost grows with the number of integrations, user roles and payment rules. Work is billed by milestone against a written scope.
Yes, when it is built properly. Node is designed for many simultaneous connections, and it scales by running more copies behind a load balancer. The usual limits are the database and slow code, not Node. We design the database, caching and background jobs with growth in mind from the first version.
We recommend it for most products. TypeScript adds types to JavaScript, which catches a class of mistakes before the code runs and makes a codebase far easier for a new developer to understand. For a founder, the benefit is practical: cheaper handovers and fewer bugs caused by one part of the system misreading another.
PostgreSQL in almost every case. It is open source, reliable and well suited to business data such as orders, users and payments, where relationships and accuracy matter. We add other stores only when there is a clear reason, such as a cache for speed or file storage for uploads.
Yes. We begin with an audit of the code, database, hosting and secrets, and give you a written list of risks in order of urgency. Sometimes a backend needs tidying. Sometimes the structure is wrong and parts must be rebuilt. We will tell you which, with reasons, before quoting.