Custom API & Backend Development

Our primary backend stack is Node.js (Express/Fastify) with TypeScript, PostgreSQL for relational data, and Redis for caching and queues. For serverless workloads, we use Vercel Edge Functions and AWS Lambda.

Yes. We frequently build adapter layers and middleware that bridge modern API standards with legacy databases, SOAP services, and proprietary data formats.

REST is simple, widely understood, and well suited to straightforward resource-based operations — the right default for most projects. GraphQL earns its added complexity when clients need to fetch varied, deeply nested data in a single request, or when multiple different front ends consume the same API with different data requirements. Choosing GraphQL for a simple CRUD API usually adds tooling and caching complexity without a corresponding benefit.

Authentication and authorisation appropriate to the risk, input validation and parameterised queries to prevent injection, rate limiting to prevent abuse and runaway costs, HTTPS throughout, and secrets held in environment configuration rather than committed to the repository. We also implement structured logging and error monitoring, because an API you cannot observe is one you cannot debug when it matters most — under load, in production.

Real scale planning means understanding where your specific bottleneck will appear, which is usually the database rather than the application layer. We design schemas and indexes for your actual query patterns, add caching where it demonstrably helps, and build stateless services that scale horizontally. We do not over-engineer for hypothetical volume — architecture built for imagined scale you never reach is a real and common cost.

Yes, and this is frequently the most valuable part of a backend engagement. We build integration layers that normalise inconsistent third-party responses into a single internal schema, with retry logic, idempotency handling, and failure logging. The difference between a robust integration and a fragile one is almost entirely in how it behaves when the upstream system is slow, rate-limited, or down — not in how it behaves when everything works.

Cost depends on the number of endpoints and data models, the number and quality of third-party or legacy integrations, authentication and security requirements, and expected traffic. Documentation and tests are scoped too. We confirm scope, deliverables and price in writing before any build work begins.