Node.js Backend Development
Backends that stay boring under load — typed services, a schema that enforces its own rules, and the observability to answer questions at 3am.
Explore this serviceOnce someone integrates, your API is infrastructure. Every field name is a commitment and every breaking change is somebody's outage. We design APIs with that lifespan in mind — clear resources, honest errors, real versioning, and documentation generated from the contract rather than written beside it.
Most API problems are not performance problems. They are ambiguity problems: an endpoint that returns a different shape depending on a query parameter, an error that says 500 when it means 'you sent the wrong date format', a field that was quietly removed.
The schema is written before the implementation, reviewed with the people who will consume it, and used to generate both the runtime validation and the documentation. The docs cannot drift from the API, because they are derived from the same source.
Rate limits that return the right headers. Idempotency keys so a retried write does not double-charge. Cursor pagination that survives inserts. Webhooks that are signed, retried with backoff, and observable by the receiver. These are the details integrators judge you on.
The situations teams are usually in when they bring us this problem.
No contract, no version, no deprecation window — and someone's integration stops working overnight.
Without idempotency, a network blip becomes a second order or a second charge. It is preventable in a day.
Hand-written docs drift within a sprint. Generate them from the schema and the problem disappears.
The same sequence on every engagement, so there are no surprises in week three.
Resources, shapes, errors and auth agreed with real consumers before implementation starts. Changing a schema is cheap; changing a live API is not.
The schema drives validation and types, so the implementation cannot quietly diverge from what was agreed.
Rate limiting, idempotency, pagination, signed webhooks, and a consistent error model — the parts people only miss when they are absent.
Generated reference documentation, a sandbox, and a versioning policy your integrators can plan around.
Concrete deliverables — all of it yours to keep, run, and hand to another team.
An OpenAPI schema, reviewed with consumers, that generates both validation and docs.
Typed handlers with a consistent error model and enforced input validation.
Rate limiting, idempotency keys, cursor pagination, and signed, retried webhooks.
Keys, OAuth or JWT with scopes — chosen for your integrators, not for fashion.
Reference docs, examples, a sandbox, and a deprecation policy in writing.
Chosen for the problem, not for novelty.
We are not tied to any of these. If your team already runs something that works, we build with it.
Schema-first with Fastify and Zod, so the contract, the validator, and the types are one artefact.
Predictable queries and indexes chosen from the slow query log, not from intuition.
Webhooks are an API too — signed, retried, and inspectable, or they will be the thing that breaks trust.
The questions that come up in almost every first conversation.
REST for public and partner APIs — it is cacheable, debuggable, and every integrator already understands it. GraphQL is a good fit when a first-party client needs flexible reads. We will make the case either way rather than default.
Yes, and it is a common starting point. We capture the real behaviour into a schema, which typically surfaces several inconsistencies worth fixing before they are written down as promises.
Additive changes are shipped without a version bump. Breaking changes get a new version, a written deprecation window, and monitoring so you can see who is still on the old one before it is switched off.
Bring the problem, not a spec. We will tell you honestly whether we are the right team and outline a concrete first step — no obligation, no sales theatre.