AI-Driven Fuel Efficiency: Transforming Airline Operations – Watch On-Demand Webinar
Did you miss our live webinar? The on-demand version of our webinar is now available! Learn how AI-driven fuel efficiency analytics can transform raw data into actionable intelligence, helping airlines optimize fuel consumption and reduce costs.
You’ll learn when an AI-driven approach is better than conventional analytics and how a multi-layer “Analytical Sandwich” approach helps you to save time. We’ll also reveal the pitfalls of Large Language Models when they lack aviation data and show how an expert-led framework ensures higher accuracy and deeper insights. You’ll get a hands-on look at FuelPro LAB, our end-to-end AI dashboard, which securely manages operational data processing analytics, protecting sensitive data without hiding key insights. Through real Fail/Pass scenarios, you’ll see why generic LLMs may fall short on airline-specific tasks and how adopting specialized intelligence, robust data structures, and advanced prompts can empower you to deliver better results faster. Join us to gain practical strategies and insights that will elevate your expertise and reshape your airline’s approach to fuel efficiency.
Webinar Highlights:
StorkJet Company and Product Overview
In this section, StorkJet presents its comprehensive solutions portfolio. You will learn more about how it tackles airlines’ operational challenges and enhances fuel efficiency. You will also discover how StorkJet’s data-driven performance models deliver complete fuel efficiency solutions for all aircraft types.
FuelPro: Fuel Efficiency Dashboard with multilayered analytical concept
In this section, the StorkJet team introduces FuelPro and shows how its comprehensive analytical dashboard efficiently manages your airline’s fuel program, supporting all flight phases, from flight planning to landing.
You’ll discover how FuelPro’s 48 predefined fuel initiatives allow airlines to monitor key performance metrics, identify fuel-saving opportunities, and proactively reduce fuel consumption. The team will demonstrate how FuelPro integrates industry-recognized initiatives and self-developed analyses in a multi-layered approach, providing airlines with the tools to track progress toward sustainability goals.
The Analytical Sandwich Framework will be a key focus, showing how its four-layer approach — combining expert oversight with AI-driven techniques — offers deeper, more accurate insights without any single layer replacing the others. Each layer has its own strengths and weaknesses, but together, they create a complementary whole.
There will be one showcase from FuelPro Lab (AI-driven analytical layer):
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- It generates a detailed taxi speed heatmap; conventional methods (dashboards and BI tools) alone would force us to oversimplify second-by-second data into simple aggregates, losing critical nuances.
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By integrating AI-driven analysis into the framework, we retain all valuable details demonstrating how each layer contributes its unique advantage to achieve a more comprehensive result.
FuelPro Lab vs. General AI
In this section, you’ll explore the differences between using FuelPro Lab and traditional Large Language Models (LLMs). While LLMs have revolutionized various industries, they often struggle with highly specialized aviation data used in fuel efficiency analysis. The current state of General AIs often lacks the domain-specific context required to provide accurate or actionable insights.
FuelPro Lab steps in to overcome these limitations by integrating StorkJet’s deep fuel expertise with the power of LLMs, creating a solution tailored specifically for operational efficiency analysis. Unlike General AImodels, FuelPro Lab understands aviation data in context. It provides actionable insights in a single, efficient query, eliminating the need for multiple, cumbersome prompts and streamlining the workflow.
To demonstrate the power of FuelPro Lab, we’ll compare it with generic LLMs using real fail/pass scenarios. You’ll see how FuelPro Lab’s aviation-focused intelligence outperforms basic LLMs in tasks such as;
- Landing Gear Extension Analysis (second-by-second QAR data)
- STAR Distance Analysis(aggregated QAR data vs OFP)
- Arrival Overburn Analysis (aggregated QAR data vs OFP),
ChatGPT would need multiple prompts and might still fail due to a lack of aviation-specific knowledge. In contrast, FuelPro Lab, with its aviation expertise, identifies these tasks quickly and accurately, much like an experienced airline analyst compared to a beginner.
By the end of this session, you’ll see how StorkJet merges AI innovation with deep airline expertise to drive better analytics, stronger operational insights, and secure data management—beyond the limits of traditional methods or General AIs.
Use link to access the on-demand webinar, or contact us to learn more.
Piotr Niedziela | VP & Head of Sales & Customer Experience
+ 48 600 800 528
