We’re excited to unveil what we’ve been working on for the past few months 🎉 In this product preview, we take a look at Charger Health, our upcoming platform designed to support charge point operators- and management systems. Here’s what you can expect: 1. Predictive Machine Learning Models 🤖 Boost customer satisfaction and reduce repair costs using our machine learning models, which predict charge point failures and detect when a charge point is at risk of going offline, enabling proactive measures to prevent downtime, failures and disruptions. 2. Advanced Data Analytics 📊 The platform provides intuitive dashboards, graphs and tables, delivering actionable insights to optimise large-scale charge point networks. Quickly uncover hidden patterns and outliers in your data to make smarter, data-informed decisions. Charger Health seamlessly integrates with existing CPMS and CPOs, combining the power of predictive ML with advanced data analytics to increase the reliability and availability of any charger network. We’re putting the finishing touches on our platform, aiming for a full launch in early 2025. Stay tuned! ⚡️
Om os
Lumina Charger Health powers EV charging with ML-driven predictive intelligence—keeping charge points online, reliable, and ready for the road ahead.
- Websted
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https://lumina-ai.dk/
Eksternt link til Lumina - Charger Health
- Branche
- Softwareudvikling
- Virksomhedsstørrelse
- 2-10 medarbejdere
- Hovedkvarter
- København
- Type
- Privat
Beliggenheder
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Primær
København, DK
Medarbejdere hos Lumina - Charger Health
Opdateringer
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𝐑𝐨𝐮𝐧𝐝𝐢𝐧𝐠 𝐨𝐟𝐟 𝟐𝟎𝟐𝟒 𝐰𝐢𝐭𝐡 𝐚 𝐟𝐞𝐰 𝐜𝐨𝐨𝐥 𝐦𝐢𝐥𝐞𝐬𝐭𝐨𝐧𝐞𝐬 2024 marks the launch of Charger Health 1.0—our predictive intelligence system designed to improve EV charger availability and reliability. ▪ Our platform is now live, ingesting data and calculating metrics in real time! ▪ We are proud that after only months of development, our machine learning models for predicting faulty and offline chargers are already showing very competitive results. ▪ Secondly, a thanks to Y Combinator (and Martin!) for inviting us to the YC startup event in London-it was an incredible experience. Both Paul Graham and the local Guinness were as brilliant as we had hoped. ▪ We’re also grateful for the generous funding we have received (Fonden for Entreprenørskab, Miljø- og energifonden af 2005, Microsoft for Startups, among others). This has allowed us to tackle the unique challenges of building and refining a system that delivers complex, real-time metrics for the EV charging industry. And lastly, but most importantly, a big thanks to our collaborators and partners for your trust and support this year. We look forward to our continued work in 2025!
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What it looks like when you receive one of those exceptional emails that everyone has to take a look at 🤩 We're thrilled and deeply grateful to announce that Fonden for Entreprenørskab has chosen to support our project with a very generous grant. This contribution is not only incredibly helpful but also serves as meaningful validation of our work and vision. We’re honored by their trust and look forward to power EV charging, with their support, and our ML-driven predictive intelligence—keeping charge points online, reliable, and ready for the road ahead ⚡️
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Enjoying our morning coffee at KU Lighthouse 🌥️ We are excited for the next couple of weeks, where we will introduce you to our platform "Charger Health", attend Digital Tech Summit and more ⚡️
I’m excited to share that I’ve teamed up with Andreas, Mikkel, and William to launch Lumina - Charger Health, a machine learning company focused on supporting the rapidly growing EV charging network. At Lumina, we’re building statistical models that predict charger downtime and failures, enabling operators to take action before problems occur. Our platform, currently in development, will provide operators with real-time OCPP data insights, offering a clear, customizable, and analytical view of their charging infrastructure and success rates. We are excited about what the future brings. You can follow our progress at Lumina - Charger Health, where we’ll share our findings and how machine learning fits into the future of EV charging infrastructure.