Airlines have the data, AINOC makes it proactive

Cargo platforms, flight operations, airport systems, and partners generate a constant stream of operational signals. AINOC (AI-Powered Cargo Control Tower) reads that data, predicts where disruption is heading, and shows ops, track and trace, commercial, IT, and leadership the same real-time picture of risk across the network.

FEATURES

Six models for a more proactive operation

Predictive Delay Engine

Predictive Delay Engine

Predicts delay time, location, and duration before the disruption cascades through the network, which gives teams room to respond.

Risk Detection

Risk Detection

Disruption signals are flagged early across weather, airspace, handling, and capacity, so teams don't rely on a single feed.

Root Cause Analysis

Root Cause Analysis

Identifies the real cause of a disruption quickly. Teams can fix the problem, not just the symptoms.

Prioritization

Prioritization

Every exception is ranked by business impact, so teams work the right shipment first instead of the loudest one.

AI Summaries

AI Summaries

AI summaries give ops and executive teams clear insights and recommended actions, without reading raw data.

Zero Rip-and-Replace

Zero Rip-and-Replace

Works directly with your existing platform, eliminating the need for new infrastructure, system migration, or parallel systems.

How it Works

Live operational data in, proactive decisions out, with no rip-and-replace

Cargo platform milestones, air traffic and weather data, airport and flight operations, partner and customer signals.

Predictive delay engine, risk detection, SLA impact analysis, root-cause AI, GenAI briefing layer.

Shipment risk summary, priority alerts, live network tracker, customer communication hub.

Getting started

The Business Case

AINOC is built to catch disruption before it becomes a missed SLA, speed up resolution, and give ops, IT, commercial, and leadership one shared, real-time picture.

  • Disruption caught before SLAs are missed
  • Faster issue resolution
  • One shared real-time picture

Pricing

Pricing follows operations rather than seats

Per airport

Per airport

Per operations center

Per operations center

Annual enterprise license across your whole network

Annual enterprise license across your whole network

Frequently Asked Questions

AINOC is an AI-powered cargo control tower that turns live operational data into proactive decisions. It brings together cargo milestones, flight and airport operations, customer commitments, and other relevant signals to create a real-time view of network performance. AINOC predicts potential delays, identifies SLA risks, and highlights the shipments and exceptions that need attention. This helps operations teams act earlier, before disruptions turn into missed service commitments.

No. AINOC is designed to work alongside your existing systems and reads the operational data your teams already generate. You don't need to replace your cargo management platform, migrate existing systems, or build separate data pipelines. AINOC adds an intelligence layer on top of your current environment. This allows teams to introduce predictive cargo operations without disrupting the systems they rely on every day.

AINOC is designed for a faster deployment because it works with data that your operation already generates. A typical pilot can focus on one hub and a couple of trade lanes within a defined live evaluation window. This lets teams test the models and assess value in a real operating environment. Once the pilot is validated, AINOC can be expanded across additional hubs, lanes or the wider network.

AINOC can be priced according to the operational scope in which it is deployed. Options include pricing per airport, per operations center, or an annual enterprise subscription covering the wider network. This allows airlines to start with a defined operational footprint and expand as requirements grow. Your account team can recommend the model based on your network, number of locations and operational needs.

AINOC gives operations, track & trace teams and leadership a shared, live view of shipment and SLA risk. By identifying potential delays and prioritizing exceptions earlier, teams can focus their attention where it matters most instead of reacting after a shipment is already missed. AI-generated summaries and root-cause insights can also help teams understand what is happening and decide what to do next. Your account team can share benchmark ranges from similar networks to help set expectations for a pilot.

Act before delays impact your customers

Operational issues rarely stay isolated. A delay can affect connections, service commitments, and customer relationships. See how AINOC can help your team identify emerging risks sooner and decide what needs attention first.

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