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Engineering the software behind ambitious businesses.

Cloud, APIs & Integration

The connective tissue between systems that were never designed to talk.

Most operational pain is not inside one system — it is in the gaps between them. Integration work is where a lot of quiet, compounding value lives.

Overview

Integration is a product decision, not just plumbing.

Two systems can be connected in a dozen ways, and the choice has consequences that outlive the project. Point-to-point is fast and becomes a web. An API layer costs more up front and keeps you able to replace either side later.

We make that choice explicitly, with the reasoning written down, because the cost of getting it wrong shows up two years later when someone needs to swap the CRM.

The same applies to what happens when things fail. Retries, idempotency, dead-letter handling and reconciliation are not edge cases in integration work — they are the job.

What you get

  • Integration architectureThe connection map, the chosen pattern and the reasoning — including what we deliberately did not do.
  • API specificationDocumented, versioned interfaces with authentication, error contracts and consumer guidance.
  • Automated pipelinesBuild, test and deploy automation across environments, with rollback.
  • Observability baselineLogs, metrics, health checks and alerts that map to real failure modes.
  • RunbookWhat to do when it breaks at 2am, written for someone who did not build it.

Scope

What this covers.

01

API design & layers

REST and GraphQL interfaces designed for the consumers that will actually use them, versioned so changes do not break clients.

02

System integration

ERP, CRM, finance, scheduling, carrier and third-party connections with proper error handling and reconciliation.

03

Cloud environments

Environment setup, containerisation, networking, secrets handling and cost-aware architecture on AWS or Azure.

04

Deployment automation

CI/CD pipelines that make releases routine rather than an event, with rollback that has been tested.

05

Observability

Logging, metrics, tracing and alerting, so problems are found before a user reports them.

06

Data exchange

Scheduled and event-driven transfer, transformation, validation and reconciliation between systems of record.

Where it fits

The problems this actually solves.

If none of these sound familiar, this is probably not the capability you need — and we would rather point you somewhere more useful.

Data is exported and imported by hand each week

Automated, validated exchange with reconciliation reporting and alerting when something does not match.

An integration fails silently and nobody notices for days

Monitoring, alerting and dead-letter handling so failures surface immediately with the context to fix them.

Every new connection is another point-to-point script

An API layer that decouples the systems, so replacing one does not mean rewriting the others.

Releases are manual, risky and done out of hours

Automated pipelines with tested rollback, moving deployment from an event to a routine.

Cloud costs are rising and nobody can explain why

Architecture and resource review with the cost drivers made visible.

Delivery

How we deliver it.

01

Map the landscape

Systems, owners, data flows, volumes, failure modes and the constraints nobody documented.

02

Choose the pattern

Point-to-point, API layer or event-driven — decided on evidence and written down with trade-offs.

03

Build & harden

Implement with retries, idempotency, validation and reconciliation from the start.

04

Instrument

Logging, metrics and alerting wired to the failure modes that actually matter.

05

Operate

Monitoring, cost review, capacity planning and ongoing support.

Technology

What we build it with.

Selected around product goals, integration needs, security requirements, team fit and long-term maintainability — not trends alone.

Cloud

  • AWS
  • Azure
  • Docker
  • CI/CD
  • Infrastructure automation

Interfaces

  • REST
  • GraphQL
  • Webhooks
  • Message queues
  • Scheduled jobs

Application platforms

  • Laravel
  • PHP
  • Node.js
  • .NET
  • WordPress & WooCommerce APIs

Data

  • PostgreSQL
  • SQL Server
  • MySQL
  • MongoDB
  • ETL & transformation
Where AI fits

Integration is what makes AI useful rather than impressive.

Assistants and automation are only as good as the data they can reach. Clean API layers, permission-aware access and reliable data exchange are the prerequisite for anything worth building on top.

Explore AI & Intelligent Automation

Questions

Straight answers.

Often yes — via database-level integration, file exchange, or a vendor's export mechanism. It is less pleasant and needs more defensive engineering, and we will be direct about the additional risk.

For two stable systems, point-to-point is frequently the right answer. The layer earns its cost once you have several consumers or expect to replace a system. We will recommend the cheaper option when it is genuinely the better one.

You do. We work within your accounts and subscriptions, with least-privilege access that can be revoked.

It is designed to fail loudly rather than silently: alerting, dead-letter queues and reconciliation reporting, plus a runbook for the on-call response.

Where does your data stop flowing?

Point at the manual export, the re-keyed field or the integration nobody trusts. That is usually the highest-return place to start.