Services
Custom integrations
We connect flight ops, crew and finance systems so data is entered once and every system agrees.
For Federal Aviation Administration (FAA) Part 135 and 121 operators and Canadian Aviation Regulations (CAR) 704 and 705 operators whose flight ops, crew and accounting systems do not share data.
In many charter operations someone on staff has become the integration, copying bookings, receipts and crew records from one system to another. We connect those systems through their application programming interfaces (APIs) and scheduled data transfers, so a record entered once shows up everywhere it is needed.
Most aviation systems were never designed to talk to each other, and some have no API at all. That used to end the conversation. Now an engineer with AI tools can read an undocumented file format, write the connector, and test it against months of real records in days, so the question is what to connect, not whether it can be done.
We build each connection with logging and failure alerts, and run it next to the manual process until the numbers match. Then the manual step goes away, and the person who had become the integration gets their hours back.
What we build
API development and integration
Connections between your flight operations platform (we work with FL3XX and JetInsight), crew records, accounting and the tools your team uses every day.
Data pipelines
Scheduled transfers that pull, clean and load data, and raise an alert when something fails instead of leaving a silent gap.
System migrations
Moving off a legacy platform with the data intact and the old system retired once the new one is proven.
How AI does the work
Connectors written fast
An API connector is mostly code that maps one system's records onto another's. The AI writes it, the engineer reviews it, and the first test runs against your real data within days.
Formats nobody documented
Engine trend monitoring files at Great North Airlines had no documentation and no API. We decoded them byte by byte with AI, connected the data to an assistant loaded with the maintenance manuals, and gave maintenance staff back four to eight hours of diagnostic work a week.
AI reads, a person approves
Where a document has to become a record, such as a licence or a medical, AI reads it and proposes the entry, a person approves it, and only then does it flow to scheduling. Every record has a human sign-off.
Every job reports in
Every scheduled transfer logs to one place and raises an alert when it fails, the same way our own overnight jobs do. A silent gap is worse than a loud failure.
How it works
- 1We map every place your team types the same data twice.
- 2We build the connection that removes the most manual work, with logging and failure alerts.
- 3We run it next to the manual process until the numbers match, then the manual step goes away.
Where we have done it
Crew records to FL3XX
When the chief pilot approves a crew record, it flows automatically to scheduling in FL3XX and to the pilot records database. Nobody types it twice.
Ramp and Business Central
Great North closes its books in Business Central. Ramp spend flows straight into it, coded against the right accounts.
Engine trend monitoring at Great North Airlines
The engine monitoring files had no documentation and no API. We decoded them byte by byte and connected the data to an AI assistant loaded with the maintenance manuals. It saves maintenance staff 4 to 8 hours of diagnostic work a week.
Questions operators ask
Which systems have you connected?
FL3XX, JetInsight, Business Central, QuickBooks, Xero, Ramp, Avinode, CAMP, ForeFlight, SharePoint, Microsoft 365, engine monitoring files and crew records databases, among others. If a system has an API we can connect it. If it only has exports, we can usually work from those.
Our system has no API. Is that a dead end?
Rarely. Scheduled exports, database access, or reading the files the system already writes all work. The engine monitoring connection started from files with no documentation and no API, decoded byte by byte and connected to an AI assistant.
How do we know the data is right?
We run the connection beside the manual process until the two match, and the connection logs every record it moves. Once the numbers agree for a full cycle, the manual step is retired.
What happens when something breaks?
The job raises an alert with the failing record instead of leaving a silent gap, and we fix it as part of the month-to-month engagement. Our own scheduled jobs report to a central log the same way, so a failure at three in the morning is known before the morning.
Do we still need the vendor's integration?
Sometimes a vendor connector is the right answer and we will say so. We build when the vendor has none, when theirs does not carry the fields you need, or when it costs more than building.
Who owns the integration?
You do. It runs in your Azure environment or ours, and the code and documentation are yours.