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Integrations between the systems you already run, engineered like production software: contracts, idempotent processing, retries, dead-letter queues and alerts, so orders, customers and invoices move on their own and stay reconciled.
Your team re-types orders, invoices or contacts from one system into another, and you want that to stop.
Sound familiar?
You need integrations you can trust in production: versioned API contracts, event-driven delivery, no duplicate side effects, tracing end to end and a runbook for when a partner system misbehaves.
Sound familiar?
What you can hold the work to, in plain terms.
Orders, customers, products and invoices flow between systems without anyone re-keying them.
A message that cannot be delivered lands in a dead-letter queue, raises an alert and is replayed after the fix.
Idempotency keys and daily reconciliation keep both sides of every flow in agreement.
Contracts, mappings and runbooks documented, so the next engineer reads a design instead of reverse-engineering scripts.
The happy path is the easy part. The design is in what happens when a partner is slow, a payload is wrong or a message arrives twice.
Sources such as an online store, a CRM and forms send events to an ingress that verifies webhook signatures and validates payloads against a schema. Events enter a durable queue ordered per record key, then workers apply idempotency keys, field mapping and retries with exponential backoff before writing to targets such as accounting, an ERP and a data warehouse. A message that still fails goes to a dead-letter queue, raises an alert to the flow's owner with the record attached, and is replayed after the fix without creating duplicates. Every record carries a correlation ID end to end, with structured logs, distributed traces, daily reconciliation and OpenAPI contracts.
The disciplines inside this service, and the detail we work to in each.
01
The right pattern for each flow: a direct API call, a webhook, an event stream, a file drop or an iPaaS recipe, chosen on volume, latency and ownership.
02
Well-designed APIs for your own systems, so partners and internal teams integrate cleanly.
03
Queues and workers that absorb spikes and partner outages without losing a record.
04
Field-level mappings agreed with the people who own the data.
05
Every record traceable from source to target, and every failure visible to its owner.
06
Common business platforms, and the systems built in-house that nobody else wants to touch.
No single pattern fits every integration. Each flow gets the one that matches its volume, its latency and the person who will maintain it.
| Pattern | Fits when | Strength | Watch for |
|---|---|---|---|
| iPaaS recipe | Fits whenLow volume, simple mapping, and a business owner who wants to change it. | StrengthFast to build and editable without code. | Watch forPer-task pricing, thin retry logic and no code review. |
| Direct API call | Fits whenOne system needs an answer from another right now. | StrengthSimple, immediate and easy to trace. | Watch forTies both systems' uptime together; needs timeouts and retries. |
| Webhooks into a queue | Fits whenEvents must never be lost, and partner systems have outages. | StrengthAbsorbs spikes; retries and replays without duplicates. | Watch forMore infrastructure to run and monitor. |
| Scheduled file or database sync | Fits whenA system has no API, or data moves in daily batches. | StrengthWorks with legacy systems nobody can change. | Watch forLatency by design, so reconciliation is essential. |
The integration design names the pattern for each flow, and why.
Every stage ends with a document you keep and a gate you can check.
Which data moves, where, how often, and who owns it.
Exit gate: A source of truth agreed for every entity that moves.
You receiveFlow diagram and data mapping
Pattern, contracts and failure handling agreed before the build.
Exit gate: Failure handling agreed for every flow, not only the happy path.
You receiveIntegration design
Built and tested against real samples, including the awkward ones.
Exit gate: Contract, replay and load tests pass on real samples.
You receiveFlows running in a test environment
Live, monitored, reconciled and documented.
Exit gate: Reconciliation is clean and your team has walked through the runbook.
You receiveMonitoring and runbook
Written down before work starts, so nothing is assumed.
The public frameworks we measure the work against, and the platforms we run it on.
A fixed, small first engagement, then the model that fits the rest.
A first engagement
A working session with the people who own each system, followed by a written design.
Fixed price
Defined projects: a website, an assessment, a migration stage
One price for that scope
Time and materials
Ongoing improvement, support and discovery work
Billed for the time used
Often, through exports, a database connection or scheduled file drops. What is possible is checked before anything is quoted.
It depends on volume, logic and who will maintain it. Tools such as Power Automate, Make or Zapier suit simple, low-volume flows; custom services suit high volume, complex mapping or strict reliability. The design says which, and why.
Messages wait in a durable queue and retry with backoff. A message that still fails goes to a dead-letter queue, its owner is alerted, and it is replayed after the fix without creating duplicates.
You do. Code, credentials and documentation are handed over, or we run the flows for you under a support agreement.
The system that owns the field. Ownership is agreed field by field during mapping; when the systems disagree, the owner's value wins and the disagreement is logged for someone to review.
It is built not to. Calls stay within each provider's published rate limits, a throttled request waits for the interval the provider asks for, and bulk work runs in batches outside busy hours.
Less often than it seems. Many real-time requests turn out to mean within a few minutes. The design states the latency each flow needs and what the difference costs to run.
Plain-language articles on integrations, with their sources.
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