Web Development

API Development & Integration

Interfaces other people can build against.

An API is a contract with people who are not in the room. They cannot ask what a field means, they will not read a long document, and once they have integrated they cannot easily be asked to change. That makes the initial design unusually consequential.

We build and document APIs for mobile clients, partner integrations, internal service boundaries and public developer platforms — including the parts that decide whether an API is pleasant to use: consistent errors, predictable pagination, sensible versioning and documentation that matches the implementation.

Most of the difficulty is not in serving the data. It is in staying compatible while the system behind the API changes.

At a glance

Typical stack: Laravel Node.js NestJS REST APIs GraphQL Redis
Common industries: Finance, E-commerce & Retail, Logistics
Engagement: Fixed scope, dedicated team, or staff augmentation

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The problem

What this solves

APIs that grow without a versioning strategy end up unable to change. Every field is potentially depended upon by a client that cannot be updated, so the only safe action is to add, and the surface expands until it cannot be reasoned about.

Inconsistency is the other tax. Errors returned in three different shapes, pagination that differs by endpoint, and dates in mixed formats each force the consumer to write special cases, and every special case is a place their integration can break.

No versioning strategy

Every field might be depended on, so nothing can ever be changed or removed.
Inconsistent errors and pagination

Consumers write a special case per endpoint, and each one is a future breakage.
Documentation that has drifted

Written by hand, out of date within a release, and now actively misleading.
No idempotency on writes

A client retry after a timeout creates a duplicate rather than resolving the original.

Our approach

How we go about it

We design the contract before the implementation, and validate it with someone who will consume it. Ten minutes of a client developer reading a draft specification catches things no amount of internal review does.

Consistency is enforced structurally: one error shape across every endpoint, one pagination mechanism, ISO-8601 timestamps in UTC, and predictable resource naming. Documentation is generated from the same definition the implementation validates against, so it cannot drift into describing an API that no longer exists.

Versioning and deprecation are decided at the start. Additive changes go into the current version; breaking changes get a new one with an announced timeline. Rate limiting, authentication and idempotency for anything that writes are designed in rather than added once someone has a problem.

Capabilities

What is included

REST and GraphQL API design
Authentication, versioning and rate limiting
Third-party and payment gateway integration
Webhook delivery and idempotent processing
OpenAPI documentation
Monitoring and alerting for integration health

Outcomes

What changes for you

Contract designed first

Reviewed by an actual consumer before the implementation makes it expensive to change.
Consistent by construction

One error shape, one pagination model, one timestamp format across every endpoint.
Documentation that cannot drift

Generated from the same specification the implementation is validated against.
Safe to retry

Idempotency keys on writes, so a timeout does not become a duplicate.

Related work

Where we have done this

All case studies

Frequently asked questions

Common questions about api development & integration.

REST or GraphQL?

REST for most cases: simpler to cache, simpler to debug, simpler to secure, and every consumer already knows it. GraphQL earns its place when clients genuinely need to compose varied queries — typically a public platform with many diverse consumers, or a mobile client fetching deep nested data over a slow connection. It also brings real work in query cost limiting and authorisation per field, which should be planned rather than discovered.

How do you handle breaking changes?

By avoiding them where possible and announcing them where not. Additive changes go into the current version. A genuine breaking change gets a new version, both run in parallel for a stated period, and consumers are told with enough notice to act. Removing an endpoint because the internal model changed, without warning, is how an API loses its users.

Can you document an API we already have?

Yes. That usually means writing a specification against the actual current behaviour — which is frequently different from the intended behaviour — and then wiring validation to it so implementation and documentation stay together from that point on. The discrepancies found during that exercise tend to be valuable in themselves.

Related services

Building an API other teams will depend on?

The contract is the expensive part to change. It is worth an hour before any of it is written.

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