What the Backend Is Actually Responsible For
Users never see the backend, which is why it is the first thing under-specified and the first thing that breaks. Its job is to hold the truth: enforce the business rules, guarantee that concurrent actions do not corrupt each other, keep an accurate history, and stay responsive when volume increases.
Most production incidents we are called into trace back to the same handful of causes: authorisation implemented only in the interface, no transaction boundaries around multi-step operations, slow queries that were fine with a thousand rows, and no record of who changed what.
What We Build
- REST and GraphQL API design, versioning and documentation
- Relational and document data modelling
- Authentication, authorisation, roles and permissions
- Background jobs, queues and scheduled processing
- Caching strategy with Redis or equivalent
- Search implementation with Elasticsearch or similar
- Payment, invoicing and financial transaction handling
- Third-party integrations with retries and monitoring
- Audit logging and data history
- Performance profiling, query optimisation and load testing
Data Modelling Is the Decision You Cannot Undo
Frameworks can be swapped and interfaces redesigned. A data model that was wrong from the start propagates into every query, every report and every integration, and correcting it later means a migration that touches everything.
So we spend time on it before writing code: what the real entities are in your business rather than what the first screen suggested, where the actual relationships lie, what must be unique, what history must be preserved, and which values are calculated rather than stored. Getting this right is the single highest-leverage hour in the project.
Correct Under Concurrency, Fast Under Load
Systems that work perfectly in testing fail in production because production has concurrency. Two people submit the same form, a payment webhook arrives twice, a scheduled job overlaps with itself, and suddenly there are two orders where there should be one.
We handle these deliberately: transactions with correct boundaries, idempotency keys on anything that can be retried, database-level constraints rather than application-level hope, and locking where genuinely needed. For performance we index against actual query patterns, eliminate the queries that multiply with row count, cache what is expensive and stable, and move slow work into queues so a request never waits for an e-mail to send.
Security and Auditability
Authorisation belongs on the server, checked on every endpoint, every time. An interface that hides a button is a usability feature, not a security control, and this is the single most common serious flaw we find in existing systems.
Beyond that: parameterised queries, validation at the boundary, secrets in a manager rather than in code, encryption at rest for sensitive fields, rate limiting, and an audit trail recording who changed what and when. The audit trail feels optional until the first dispute, at which point it is the most valuable thing in the database.