Mako AI Days 2024, DAY 1: "Me, myself and AI" - Sebastian Urbański, Project Manager, MakoLab

In this engaging presentation, Sebastian Urbański, Project Manager at MakoLab, shares a practical example of how AI can be used to optimize processes and improve efficiency. The talk focuses on a small yet impactful AI implementation that streamlined vehicle diagnostics for a client, saving time and resources while enhancing productivity. This case study demonstrates how even modest AI solutions can deliver significant results without requiring extensive computational resources or cloud services. Here are the presentation’s key highlights and takeaways:
🟡 Small AI implementations can have a big impact, improving efficiency and saving time without requiring significant resources.
🟡 Process analysis and collaboration with business analysts are crucial for identifying bottlenecks and designing effective solutions.
🟡 Lightweight AI models can be deployed securely on local systems, addressing concerns about data privacy and cloud dependency.
🟡 The success of this project highlights the importance of tailoring AI solutions to specific client needs, focusing on practical and measurable outcomes.
📌 Key Highlights:
🟡 The Challenge:
A client faced capacity issues, processing around 180 vehicle expertise requests per month. The diagnostic process was time-consuming and inefficient, creating a bottleneck in their operations.
🟡 The Solution:
MakoLab developed a lightweight AI-powered mobile application that streamlined the process of vehicle damage assessment. The app allowed experts to take photos of vehicle damage, which were then analyzed by an AI model in the background. The results were seamlessly integrated into the client’s existing systems for further processing.
🟡 Efficiency Gains:
The new solution reduced the time required for preparing expertise diagnoses by 15-20 minutes per case, saving the company approximately six working days per month. This improvement was achieved without overhauling the entire workflow.
🟡 Rapid Implementation:
The project was completed in just five months, from initial analysis to deployment, showcasing the potential for quick and effective AI integration.
🟡 Cost-Effective and Secure:
The AI model was designed to run on minimal hardware, eliminating the need for cloud services and ensuring data security-an essential factor for companies handling sensitive information.
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