Category: Participant 2024
LoopIt.ai
We are currently seeking internship student(s) who are keen to work in a multi-disciplinary & multi-university team with external stakeholders. Currently pursuing a BSc or MSc degree in: - Artificial Intelligence and Engineering Systems - Computer Science and Engineering - Data Science and Artificial Intelligence - Data Science in Business and Entrepreneurship - AI and Digital Innovation - Artificial Intelligence Engineering Systems - Computational Engineering - Other Related Fields. Preferred, knowledge in: Machine Learning, Google Colab and Python. Optional: Android Studio (Kotlin), MySQL (or any other DB).
Contact usAt LoopIt.ai we're tackling an age old problem: what to do when your car is damaged or needs repair? Our mission is to introduce automation into the traditionally manual, labour-intensive, and expensive processes that currently impacts the automotive industry. These processes often involve multiple systems, leading to inefficiencies, delays, and frustration for drivers. Our Goal: Simplify and Automate - The Repair and Claims Journey within the Automotive Industry. Streamlined Repair Process: We aim to simplify the repair journey for car owners and leasing companies. No more enduring delays or drowning in paperwork. Our automated system ensures a smoother experience. Efficient Claims Handling: Dealing with insurance companies, repair shops, and leasing companies can be a headache. LoopIt.ai streamlines communication, making the claims process more efficient. ___________________________________________________________________________________ What do we seek? We seek partnerships with: Car Manufacturers, Car Leasing Companies, Car Insurance Firms, Car Repair Shops and Financial Institutes. ___________________________________________________________________________________
Industry Overview: The automotive repair industry is valued at €199.56 billion and is projected to grow by 1.9% to reach €227.60 billion by 2030. Notably, 40.8% of automotive repairs occur within the European Union, driven in part by 3.4 million annual accidents as of 2022. Where the average age of vehicles is increasing from 12 to 17 years. ___________________________________________________________________________________ Case Study Insights: In a specific case study, an automotive repair chain with 80 outlets in the Netherlands currently spends at least €16.8 million annually on internal costs for manual damage assessment, covering 160,000 vehicles yearly. This current method is not only costly but also inefficient, requiring 12 steps that can take up to 9 weeks to complete before an appointment for damage assessment can be made, after which the repair work can start. ___________________________________________________________________________________
To address these inefficiencies, we are developing a mobile application that reduces the process to 7 steps, taking only 15 minutes to complete for the end-user. Our solution developed on machine learning models & artificial reality is projected to save €13.6 million in the examined case, enhancing both cost-effectiveness and time efficiency. The proposed solution integrates customers (end-user / drivers), leasing companies, insurance providers, and the repair industry into a single end-to-end platform, potentially increasing the capacity to assess and repair an additional 52,280 vehicles annually for the examined case. ___________________________________________________________________________________ Broader Impacts and Scalability: This capability not only frees up resources but also facilitates business expansion. Given that the issues (of damage assessment) addressed by the solution are not confined to a single geographic area, we have developed a highly scalable growth model. Hence the benefits of the solution can not only help the end-user (convince) they can also help the insurance companies receive accurate damage (claims) assessments, leasing agencies manage their vehicle fleet and help the auto body repair shops to utilize their resources effectively. Thus we view our proposition as a disruptive technology to current practices. ___________________________________________________________________________________ Current Stage of the Solution: We have completed the Prototyping stage, have created a small Technology Demonstrator and are moving towards the Patenting Phase. ___________________________________________________________________________________ Keen to know more? Either Contact Us or visit our website www.loopit.ai