Aviation Intelligence & Data Aggregation Platforms
Aviation intelligence is the layer that turns raw schedules, live positions, and operational notices into answers: which flights will be late, which airports are under strain, which routes are growing. AeroCraft builds automated aggregation platforms that collect those feeds, reconcile them, and surface the decisions they support in dashboards, alerts, and APIs.
Stop relying on fragmented information. We build automated data aggregation platforms that transform complex global schedules and operational feeds into clear, actionable business insights.
What is the difference between aviation data and aviation intelligence?
Data is a departure time, a position report, or a NOTAM. Intelligence is the conclusion those records support: this inbound aircraft is running 40 minutes late, so the outbound rotation is at risk; this runway closure will push arrivals to the secondary airport tomorrow morning. Most organisations already have the data. What they lack is the automated layer that connects it and states the conclusion before a person has to go looking.
What does an aviation intelligence platform do?
We build platforms around four functions: aggregate, reconcile, predict, and deliver.
- Aggregate — continuous collection from schedule, tracking, status, and notice feeds, with gaps and outages detected automatically
- Reconcile — conflicting sources resolved into a single flight and airport state, with provenance kept for every field
- Predict — machine-learning models for delays and disruption, trained on historical schedules and actual movements
- Deliver — the result exposed where it is used: operational dashboards, threshold alerts, scheduled reports, and APIs
How does machine-learning delay prediction work?
Delay prediction combines a flight's own history with the live state of the network around it. Models learn from historical schedules and actual movements — how a route, carrier, aircraft type, and airport behave at a given time and season — and then adjust in real time using the current position of the inbound aircraft, the congestion at origin and destination, and active operational notices.
The useful output is not a single number. It is a prediction with a confidence band and the reason behind it, so an operations team can act on it or ignore it with a clear view of the risk.
Has AeroCraft built this before?
Yes. Skyinfo is our own global flight intelligence platform. It covers 7,883 airports, 233 countries, and more than 500 airlines with 24/7 live data, and combines real-time tracking, machine-learning delay predictions, and airport health indicators. It serves everyday travellers, airport operations teams, and airlines, and offers API access to developers.
Client platforms are built on the same components, adapted to the questions your teams actually need answered.
How do you decide which questions the platform should answer first?
We start with the decisions your teams already make under time pressure and the information they wish they had at that moment. Operations controllers usually want earlier warning of disruption; commercial teams want to see competitor schedule changes as they happen; airport teams want to know how busy the next few hours will be. Each candidate question is scored on how often it comes up, how costly a late answer is, and whether the data to answer it is available.
The highest-scoring question becomes the first release. Its dashboard and alerts go live, usage is measured, and only then is the next question added. That way the platform earns its place one proven answer at a time, instead of launching as a large system nobody has asked for.
Frequently asked questions
Can the platform be private to our organisation?
Yes. Client platforms run in your environment or a dedicated tenant, combining public aviation feeds with your internal operational data.
Do we need our own data science team?
No. AeroCraft builds, trains, and monitors the models. We document them so an in-house team can take ownership later if you want.
What does a first deliverable look like?
Usually one dashboard and one alert stream answering a single high-value question — for example, which next-day departures are at risk — before the platform is widened.
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