seer® is an advanced airport intelligence solution that uses real-time video feeds and AI analytics to monitor aircraft turnaround processes and improve operational efficiency. Its key benefits include:

• automated detection of pivotal events such as on-block, GPU connection, stairway arrival and pushback;

• seamless integration with systems like AODB and A-CDM for live alerts and proactive interventions.
  The platform also offers predictive analytics such as off-block time forecasting to support resource allocation and enhance punctuality. Additionally, seer® ensures data security through a hybrid edge-cloud deployment and can leverage existing camera infrastructure to minimize implementation overhead.

Our Food Waste Tracker is a Computer-Vision-AI solution that installs a compact camera at tray return areas to detect and analyse every uneaten meal, turning leftover trays into actionable data.It provides item-level insights into food waste by identifying which meals and components were left behind and estimating the weight and CO₂ footprint of those leftovers.

Key benefits include:

• Lower food costs through reduced over-production and better menu-planning.

• Enhanced sustainability by tracking and reducing CO₂ emissions tied to food waste.

• Customised dashboards for catering, lounges and inflight services that support ESG and Net-Zero targets.
  With a plug-and-play design that can be deployed in just 4–6 weeks and operated on existing infrastructure, the system gives airlines and caterers real-time intelligence to improve passenger experience while cutting waste.

Our Luggage Tracker uses advanced computer-vision technology to monitor carry-on luggage at e-gates and link each detected bag to passenger boarding passes in real-time. It delivers critical insights by:

• detecting how many bags passengers bring and identifying oversized or non-compliant carry-ons;

• enabling gate agents to act early with configurable alerts to prevent conflicts and boarding bottlenecks.
  The system forecasts boarding duration and turnaround time more accurately, supporting operational planning and cost reduction. Additionally, it’s designed for rapid deployment via a single camera per gate, scalable cloud or edge architecture, and integrates with existing airport infrastructure.

Crew Management Solution

The solution brings data-driven crew scheduling and management into your airline’s daily operations by applying machine learning to crew demographic, operational and rostering data.
Its benefits include:

• creating more realistic scheduling scenarios that take into account fatigue, crew availability and historical patterns;

• producing a more stable, reliable roster that boosts crew satisfaction and reduces last-minute disruptions.
  It ensures operations remain efficient and compliant—by optimising end-to-end scheduling while respecting ethical/ GDPR considerations—so airlines can improve both performance and employee experience.

The solution applies advanced machine learning (neural networks) to help airlines predict demand across their network more accurately than traditional linear regression models.
It allows airlines to personalise ancillary pricing and steer inventory automatically by analysing complete network data and detecting non-linear patterns such as holidays, competitor pricing moves and unexpected demand shifts.
Key benefits include:

• substantially more accurate demand forecasts (reducing manual steering activities by up to -80%), and

• revenue uplift (e.g., direct EBIT gains of +3%)
  It’s cloud-native, scalable to large data volumes, integrates with existing IT setups, and is designed with user-centric workflows so revenue management teams can adopt it with minimal friction.