API Development & Integration Services

Who brings us API work

Several apps, internal tools or outside companies need the same data and actions, and without a clear, versioned API every new connection becomes a fragile one-off.

SaaS companies opening their product to customers' developers through a public API
Teams whose web and mobile apps each talk to the database differently
Businesses exchanging invoices, stock levels or bookings with suppliers' and customers' systems

APIs other systems can depend on

An API is a contract. Web and mobile apps, internal tools and third-party systems all depend on it, so one careless change can break several products at once. We design and build REST and GraphQL APIs, integration layers and backend services, with versioning, authentication, rate limits and documentation planned from the start. AI agents help implement endpoints, draft contract tests and keep docs in sync with the code; engineers own the API design, data model, security and every change that ships.

AI-assisted, expert-led API engineering

How AI assists

Implementing endpoints, validation and data access from the agreed OpenAPI or GraphQL schema
Drafting contract, integration and negative tests directly from the specification
Reviewing logs and traces to help locate slow queries, timeouts and failing calls
Keeping reference docs, code examples and changelogs in step with the code

What our experts own

Engineers design resources, schemas, versioning and error formats, and review every change before merge
Engineers decide authentication, authorization and what each client may access, following OWASP guidance
QA tests permissions, invalid input, rate limits and failure behavior, not only the happy path
DevOps manages environments, secrets, controlled releases and production monitoring

What you receive

What we deliver for your API

API design and specification
An OpenAPI specification or GraphQL schema agreed before implementation, covering resources, errors, pagination and versioning.
REST and GraphQL implementation
Typed, tested endpoints and resolvers with input validation, consistent responses and efficient database access.
Authentication and access control
OAuth, OpenID Connect, API keys or token-based sessions, with role-based permissions checked on every endpoint.
Rate limiting and abuse protection
Per-client limits, quotas and clear throttling responses that protect your API and the services behind it.
Third-party integrations
Connections to payment, messaging, CRM or ERP systems, with webhook handling, retries and idempotency built in.
Developer documentation
Interactive reference docs, examples, error catalogs and changelogs, generated from the specification and kept current.

Scope, preparation and support

Start with a defined scope
Start with a defined exchange between named systems: CRM records, payment events, orders or another business object. Agree the source of truth, API contract, exceptions and test cases before expanding to more connections.
What you provide
Provide current API documentation, sandbox access, sample payloads, field mappings, expected volumes and the owners of each system. Flag vendor approvals, licensing restrictions and missing endpoints before estimating.
Support after delivery
Delivery includes integration code, configuration, contract tests and recovery notes for the agreed flows. Version changes, credential rotation, monitoring and incident response can be covered by a separate support plan.

How a request moves through your API

Illustrative path for one write request; real APIs add or skip steps depending on the design.

Client call
A web app, mobile app or another company's system calls a documented endpoint with credentials.
Gateway and auth
The token or key is verified, rate limits applied and the caller's permissions checked.
Checkpoint: Unauthorized calls stop here
Service logic
Business rules run on validated input; idempotency keys stop a retried request from acting twice.
Checkpoint: Input checked against the agreed schema
Data and queue
The change is saved to the database; slow work goes to a queue instead of delaying the response.
Webhooks and consumers
Signed events notify subscribers, such as billing, search indexing or a customer's webhook endpoint.

When something fails: Failed jobs and webhook deliveries retry with backoff, then move to a dead-letter queue, where an engineer inspects and replays them.

Typical API requests

Typical scenarios we scope, not client case studies.

Public API for customers' developers
A SaaS company's customers keep asking for programmatic access to their own data. We would design scoped API keys, pagination and webhooks, publish a sandbox with test data, and write a deprecation policy before the first version goes public.
One backend for web and mobile
A web app and a mobile app each query the database their own way, so the same rule behaves differently on each. We would move the shared rules behind one API and switch each app over screen by screen.
Reliable exchange with a supplier's system
Stock updates from a supplier arrive as emailed CSV files that staff copy in by hand, sometimes twice. We would agree an API contract with the supplier's developers, accept updates through an authenticated endpoint and reject duplicates using idempotency keys.

How an API project runs

01
Define the contract
We agree consumers, resources, authentication and error handling, then write the OpenAPI or GraphQL schema and review it with your team.
02
Build against the spec
Coding agents implement scoped endpoints and engineers review each change. Mock servers let your web and mobile teams start integrating early.
03
Test and secure
Contract, integration and load tests, plus permission and input checks based on OWASP guidance. Findings are fixed and retested before release.
04
Release and monitor
Controlled deployment with docs published, monitoring and alerts live, and a deprecation plan ready for any future breaking change.

Two ways to work with AI tools

Choose where AI coding agents may process your code while we build. The engineering standard is the same either way.

Private / Local AI Engineering
Privately hosted models inside infrastructure you control or an agreed isolated environment.
Discuss with this package
Claude Code / OpenAI Codex Engineering
Claude Code and/or OpenAI Codex with cloud settings your organization approves.
Discuss with this package

Not sure? We'll recommend one during scoping. Compare AI delivery options

How design, QA and operations connect

Designed for developers and users
Consistent naming, predictable errors and clear docs are designed in from the start. Where the API serves a product, designers make sure errors become clear messages for users.
Contract and permission testing
QA runs contract tests on every change and checks roles, permissions, invalid input and rate limits, to catch breaking changes before release rather than in production.
Observable in production
Structured logs, metrics, tracing and alerts on error rates and latency, with controlled deployments and a rollback plan for every release.
Versioning and ongoing care
We manage versions and deprecations with notice and migration guides, and can keep the API patched, monitored and improving under an agreed support plan.

Where API work hands off

The web or mobile apps that call the API are scoped separately — see Web Design & Development or Mobile App Development.
An independent security assessment of an API you already run is a separate engagement — see API Security.
If two SaaS tools already offer ready-made connectors, linking them may need no new API — see Zapier Integration.
Third-party APIs' availability, limits and pricing stay with their providers; we design around them with retries, caching and alerts.

FAQ

Frequently asked questions

REST or GraphQL: which is right for us?

REST is a sound default for public APIs, resource-style data and broad client support, and it is simple to cache. GraphQL fits products with many related data types and clients that need different shapes of data, such as web and mobile apps sharing a backend. Some systems use both. We recommend one based on your consumers, data and team.

How do you handle versioning and breaking changes?

We avoid breaking changes where possible, for example by adding fields instead of changing them. When a breaking change is necessary, we publish a new version, announce the deprecation, provide a migration guide and keep the old version running for an agreed period while monitoring who still uses it.

Can you integrate the API with our existing systems?

Yes. We build integration layers for CRMs, ERPs, payment providers, legacy databases and internal services. We map data and ownership first, then design retries, idempotency and reconciliation, so failures are visible and recoverable instead of silently losing data.

Do AI tools see our API keys or production data?

Coding agents work on code and test data, not production secrets, and they don't get unrestricted access to live systems. With Private / Local AI Engineering, models run on your infrastructure or in an agreed, isolated environment. With Claude Code / OpenAI Codex Engineering, commercial agents process code under account terms and access we agree before work starts.