API design & layers
REST and GraphQL interfaces designed for the consumers that will actually use them, versioned so changes do not break clients.
Cloud, APIs & Integration
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
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.
Scope
REST and GraphQL interfaces designed for the consumers that will actually use them, versioned so changes do not break clients.
ERP, CRM, finance, scheduling, carrier and third-party connections with proper error handling and reconciliation.
Environment setup, containerisation, networking, secrets handling and cost-aware architecture on AWS or Azure.
CI/CD pipelines that make releases routine rather than an event, with rollback that has been tested.
Logging, metrics, tracing and alerting, so problems are found before a user reports them.
Scheduled and event-driven transfer, transformation, validation and reconciliation between systems of record.
Where it fits
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
Systems, owners, data flows, volumes, failure modes and the constraints nobody documented.
Point-to-point, API layer or event-driven — decided on evidence and written down with trade-offs.
Implement with retries, idempotency, validation and reconciliation from the start.
Logging, metrics and alerting wired to the failure modes that actually matter.
Monitoring, cost review, capacity planning and ongoing support.
Technology
Selected around product goals, integration needs, security requirements, team fit and long-term maintainability — not trends alone.
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 AutomationQuestions
Point at the manual export, the re-keyed field or the integration nobody trusts. That is usually the highest-return place to start.