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Empowering Airport Operations with AI

An evolution for airport operations, integrating data from building systems, IoT applications, and cloud sources. Our platform enhances operational efficiency, ensures safety protocols, optimizes resource allocation, and improves passenger experiences. Airport operators can navigate the complexities of modern airport management, making informed decisions based on near real-time data.

The Power of IDL (Independent Data Layer)

The Independent Data Layer (IDL) is a robust data management platform that plays a crucial role in collecting, integrating, and analyzing real-time data from various sources within an airport.


The IDL gathers a diverse range of data, including HVAC systems, electrical telemetry, and flight data. It collects data on energy usage, passenger density, electrical loads, and flight schedules, among other things.

Abstract Sphere
Billions of data points analyzed in near real time...


Cloud Sensor Integrations


Geospatial Formats


Enterprise / Facility



Device Mappings

The CA3 is a powerful tool that can automate a variety of processes at airports. From optimizing HVAC settings to predicting energy needs based on flight data, it can help streamline operations and improve efficiency. CA3s can provide valuable insights for strategic gate planning and aircraft turnaround time optimization.


Continuous data gathering

IDL is a cutting-edge AI-powered data layer designed for commercial and industrial spaces. It enables property owners, facility operators, and solution providers to access real-time data from building systems, sensors, devices, and vendor APIs with ease. By automating the data discovery, extraction, and normalization process, IDL simplifies data integration using machine learning. Additionally, the open-source data model ( creates an independent data layer that is both efficient and effective.


Continuous monitoring

Cognitive Autonomous AI Agents, or CA3s, continuously monitor the Independent Data Layer (IDL) by utilizing advanced algorithms and machine learning techniques. They are designed to process and analyze the vast amounts of data gathered by the IDL in real-time.


CA3s constantly scan the IDL for changes, trends, and anomalies. They analyze data from various sources such as server usage, network traffic, weather, temperature, and humidity. This continuous monitoring allows CA3s to provide real-time insights and suggest informed decisions.


Autonomous AI Optimizations

AI automation has become a game-changer in various sectors, including architectural design, sustainability metrics, project management, and facility management. With the use of advanced algorithms and machine learning techniques, Cognitive Autonomous AI Agents (CA3s) can automate complex decision-making processes, reducing costs and enhancing operational efficiency.


This allows teams to focus on more strategic initiatives, improving overall productivity and effectiveness. Additionally, AI automation plays a crucial role in sustainability efforts, minimizing carbon emissions and optimizing resource utilization. In facility management, CA3s are projected to be key players in this growing market, contributing to increased efficiency, cost savings, and improved decision-making.


Our AI approach in airport operations can bring strategic benefits by improving operational efficiency and energy management. By optimizing HVAC settings and electrical loads, it can reduce energy consumption and costs. The insights provided by the CA3 can also support decision-making, helping airport operations teams manage their facilities more effectively. Predictive maintenance capabilities can reduce downtime and ensure uninterrupted operations.



My name is Alex

I am a Cognitive Autonomous AI Agent. Lets chat about this, or any other question you may have...

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