integration
Middleware between the systems your business runs on. Orders, stock, invoices, statuses and documents moving between platforms that were never designed to meet, validated on the way through, and logged so you can see exactly what happened. There are plenty of off-the-shelf connectors; we're the people you call when none of them quite fit.
What it looks like from where you're sitting
Someone exports a CSV from one system and imports it into another every morning. When they're off, it doesn't happen.
A big customer wants to send orders by API. The system you run the business on only understands flat files, or a screen. The conversation stalls.
There's an integration already. Nobody knows how it works, it fails quietly, and the person who built it has gone.
What we do about it
Every field on one side matched to its meaning on the other, written down, versioned, and changeable without redeploying anything.
Bad data gets stopped at the door with a clear reason, not passed through to break something downstream. Rejections are visible and actionable.
REST, SFTP, EDI, webhooks, email attachments, whatever each system speaks. Both directions. Retries and back-off when the other end is down.
Every message in and out, searchable. When a customer asks where order 48213 went, the answer takes thirty seconds, not an afternoon.
Failures, backlogs and silences reported to people who can act, before the customer notices.
Hosted, monitored, patched and supported. New customer connections added as standard work, not as a project.
For the technical reader
Message-oriented: every inbound document becomes a record with a lifecycle (received, validated, transformed, delivered, acknowledged, failed) so nothing is lost between steps and everything can be replayed. Transformations are configuration, not code, so a new customer format is a mapping file rather than a release.
Failure is the normal case we design for: idempotent handlers, dead-letter queues, explicit rejection reasons sent back to the source, and dashboards that show queue depth and age. Deployed through a pipeline, with the schema and mappings under version control.
A UK 3PL with many customers, each sending orders their own way over SFTP, REST or EDI, and one warehouse system that spoke one language. We built the layer in the middle: per-customer mappings, validation with reasons sent back, full logging, confirmations and stock flowing the other way. It has run the operator's daily order flow unattended for years, and a new customer is a mapping, not a release.
Tell us which systems and what moves between them. We'll tell you what the middle layer would look like and roughly what it takes.