Amygda AI

While AI enhances maintenance capabilities, human expertise remains irreplaceable – it's about augmentation, not replacement. 🚁 We discussed AI's transformative role in helicopter maintenance in the Vertical MRO Podcast. Some key points we covered: • Less than 10% of helicopters worldwide currently use health and usage monitoring systems (HUMS) • The role of AI in preserving crucial technical knowledge as experienced engineers retire • The "iPhone Moment" for AI in Maintenance Listen to the full podcast - link in the first comment. What are your thoughts on the future of AI in helicopter maintenance?

Generative AI and classical AI will cut costs.  But how do you measure ROI on AI projects which require investing at start? In our Guide for Integrating Generative AI in the Transport Industry we share insights on ROI learnt through customer discussions. Note: AI projects have upfront costs that may lead to negative ROI in the first year, but can become positive in as little as 18 months, as the benefits accumulate. Download the Guide and find our ROI calculator inside - link in the first comment.

Just published a piece on how AI is transforming baggage handling systems in airports 🛄 The challenge is clear: service engineers spend hours analysing vast amounts of data to diagnose issues in these complex systems. Every minute of downtime impacts passenger experience and airport operations. Here's what our AI agent does differently: 📶 Processes daily data to identify anomalies early 🎯 Pinpoints equipment likely responsible for alerts 🖥️ Provides clear visualisations of relevant data 𝗧𝗵𝗲 𝗿𝗲𝘀𝘂𝗹𝘁? 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝘀 𝗰𝗮𝗻 𝘀𝗮𝘃𝗲 𝘂𝗽 𝘁𝗼 𝟳𝟬% 𝗼𝗳 𝘁𝗵𝗲𝗶𝗿 𝘁𝗶𝗺𝗲 𝗮𝗻𝗱 𝗰𝗮𝘁𝗰𝗵 𝗽𝗼𝘁𝗲𝗻𝘁𝗶𝗮𝗹 𝗶𝘀𝘀𝘂𝗲𝘀 𝘁𝘄𝗼 𝘄𝗲𝗲𝗸𝘀 𝗯𝗲𝗳𝗼𝗿𝗲 𝘁𝗵𝗲𝘆 𝗰𝗮𝘂𝘀𝗲 𝗱𝗶𝘀𝗿𝘂𝗽𝘁𝗶𝗼𝗻𝘀. Curious about improving your airport's baggage handling reliability? Let's talk about how AI can support your maintenance and ops teams. Link to article in the first comment. 

"As AI continues its accelerating influence on workplace evolution, empowering teams with effective decision-making is a key enabler for success." - Joe Yaeger, Rheinberry Download our free Generative AI Guide and explore ways for the Transport industry to modernise and innovate with the help of Generative AI technologies: 🔑 Gain insight from industry experts 📊 Use our AI calculator 🔎 Explore the potential of AI in transport ✅ Guidelines for ethical AI deployment Download the Guide here: https://lnkd.in/eG7vtfQC

Helicopters generate vast amounts of data.  Using AI to analyse this data is more efficient than manual analysis alone. This data holds huge potential for improving safety, efficiency, and operational costs. However, the sheer quantity of information presents a significant challenge for traditional analysis methods. AI identifies patterns and correlations that human analysts might miss. Amygda's human-in-the-loop approach ensures that AI’s power is harnessed responsibly and effectively. Read more on AI for Helicopter Maintenance in this Vertical Magazine article featuring Amygda: https://lnkd.in/eQFax6VN

Amygda AI has AI Agents working in airport Ops Not massive AI systems trying to do everything. Something that's computationally smarter. Agents that focus on one thing each: ✅ Agent watching system patterns ✅ Reading maintenance patterns ✅ Connecting patterns with likely outcomes This avoids need for years of data to begin with. The removes complex integration projects. Just agents learning from day 1. This is how airports integrate artificial intelligence. Today. Not in months and months of model training and years of implementation. I think this is a design pattern for other transport industries too, but slightly different based on the actual data stack that exists. #TransportAI #AI4Airports

AI can understand language.  Amygda AI is building AI to understand 𝘮𝘢𝘤𝘩𝘪𝘯𝘦 𝘭𝘢𝘯𝘨𝘶𝘢𝘨𝘦. LLMs can already: ✅ Learn patterns without seeing every possibility ✅ Transfer knowledge across contexts ✅ Build relationships, not just follow rules We're applying these same principles to engineering operations. Combining asset data with MaintOps data completes the Machine Language Understanding. Instead of feeding an AI system years of historical failures, we're teaching it to understand the 'language' of machines. When a maintenance engineer writes "bearing sounds rough during startup," that's valuable context. When a similar pattern appears in a different system weeks later, that connection matters. There's so much value in the untapped maintenance and operations data in the transport world! #TransportAI #MaintOps #MachineIntelligence

We explore the challenges for managing baggage and security systems at airports and testing the potential of Generative AI with respect to reliability. Using this approach airports can realise the following benefits: 🔎 Real-time anomaly detection for smoother operations ⚙️ Root cause analysis 💡 Continuous monitoring and feedback loop Article co-authored by Richard Dempers PhD CEng MSc BEng and Joe Yaeger from Rheinberry. Read more: https://lnkd.in/eR77gX56

Faizan Patankar was one of the panellists on the Vertical MRO podcast, talking about the future of AI-human collaboration in Maintenance 🎯  Some insights from the conversation: - Did you know helicopters generate 4,000 data points per second? That's where AI becomes crucial for maintenance teams - Less than 10% of helicopters worldwide use health monitoring systems - showing the massive potential for innovation in this space - The future isn't about replacing human expertise - it's about augmenting it with AI to make better maintenance decisions 🎧 Listen to the full episode and learn about "the iPhone moment" for AI and Maintenance, and how many dimensions the human brain can actually process! https://lnkd.in/e3ZdRAaw

AI makes errors. Humans too make errors. On a recent panel discussion with Aviation Week, I wanted to bust the myth that AI has more errors. Having looked at some of the big predictive maintenance platforms, there are hundreds of people who manually review what an alert or prediction is saying before it gets sent to customer. Prediction errors have existed for years, but you just haven’t seen them because you’ve been shielded. We are building artificial intelligence assistance for MaintOps teams to improve reliability and boost efficiency. The use of AI is to do the processes efficiently. Without needing to hire 100s of people to manually review data. https://lnkd.in/e5V4TUgf