In aviation maintenance, up to 80% of valuable data can remain hidden and underutilised. This challenge can lead to inefficiencies and missed opportunities for optimisation. Leveraging advanced AI technologies can transform this unstructured data into actionable insights, improving overall maintenance outcomes without additional staff.
Amygda’s Maintenance AI Assistant addresses these challenges through Generative AI technology to support maintenance troubleshooting and knowledge management in a conversational interface, pointing to contextual information and sources.
In addition, the Maintenance AI Assistant structures unstructured data and retrieves information from images and documents, specifically within the aerospace domain and working practices.
Here are the three themes we see developing and in test with maintenance AI assistants currently in the aviation industry.
#1/ Maintenance AI Assist automates manual processes and integrates data sources
AI can automate labour-intensive processes such as data entry and report generation, and integrate disparate data sources. This provides a unified, comprehensive view of maintenance activities, allowing for streamlined workflows and better decision-making.
The example below is of Amygda’s Airline Maintenance AI Assistant which checks the initial alert and runs a series of follow-up checks which otherwise a human would have to do—saving hours by doing these in minutes.
#2/ Freeing up valuable technician time
Airlines are facing labour shortages. Technicians are key, in every transport sector. It’s one reason we heavily focus on Maintenance AI Assistant for airlines.
By handling routine tasks, AI allows technicians to focus on more critical maintenance issues, enhancing overall productivity and efficiency. This shift optimises resource allocation, reduces operational costs, and improves aircraft availability.
#3 / Real-time insights and knowledge management through Maintenance AI Assistant
Generative AI supports maintenance troubleshooting through a conversational interface, pointing to relevant contextual information and sources. It structures unstructured data and retrieves information from images and documents, specifically tailored to the aerospace domain. This capability bridges the gap between maintenance insights and teams taking the right troubleshooting steps.
By unlocking and utilising hidden maintenance data with AI, airlines can achieve significant improvements in efficiency, decision-making, and overall operational performance.
Maintenance AI Assistant is available for testing on the cloud or securely without using ChatGPT models.
By unlocking and utilising hidden maintenance data with AI, airlines can achieve significant improvements in efficiency, decision-making, and overall operational performance. Amygda’s Maintenance AI Assistant is designed to meet these needs, bringing advanced AI capabilities to the forefront of aviation maintenance.
If you’re interested in learning more about how our AI-powered solutions can benefit your operations, visit our website and explore what Amygda can do for your airline.
Read more on Amygda’s AI-powered OEM-agnostic maintenance for Airlines.
