1. AI-Based Predictive Maintenance
We developed an AI-powered predictive maintenance system that monitors machinery health through vibration and temperature data. By detecting early warning signs of mechanical failures, the system enables proactive maintenance planning and minimizes unexpected downtime. This smart maintenance approach led to a significant cost reduction of €250,000 in just one year.
2. Fake Defect Detection Using Big Data
In manufacturing environments, visual inspection systems can wrongly label products as defective due to environmental factors like dust or lighting. We tackled this with a deep learning solution that processes image frames and identifies true versus false defects with high accuracy. The system has been tested on over 8000 materials, drastically reducing unnecessary rework and improving production quality.
3. Spare Parts Optimization
This project focused on optimizing spare parts inventory through data analytics. Our AI solution determines ideal stock levels, prevents obsolescence, and improves warehouse efficiency. By avoiding excess inventory and minimizing stockouts, the company achieved a saving of €300,000 in one month.
4. AI-Based Fastener Recognition
We built a mobile AI solution capable of identifying 2,000+ fasteners from camera input. The app classifies fasteners by dimensions, standards, and part codes, and recommends inventory matches for custom pieces. This tool speeds up procurement and helps technicians instantly identify correct parts on-site.
5. AI-Based Recipe Generator (Predictive Quality)
In collaboration with Maxion Wheels, we developed an AI model that recommends optimal production recipes to reduce scrap in wheel manufacturing. By learning from production line data, the system achieved a remarkable reduction in scrap rate—from 5.2% down to 1.6%—leading to improved quality and significant material savings.
6. AI-Based ECG Analysis
Our AI system analyzes ECG signals to detect irregularities that may indicate cardiovascular disease. By learning wave patterns and timing intervals (P-QRS-T complex), the solution supports early diagnosis and improved clinical decision-making. It assists doctors and analysts in interpreting complex heart data efficiently.
7. AI-Based Sales Forecasting
We partnered with DATAKOD to forecast product sales using advanced time series analysis techniques such as ARIMA, SARIMA, LSTM, and FB-Prophet. This solution accounts for seasonality, trends, and anomalies in sales data, enabling businesses to make accurate forecasts across thousands of products and optimize supply chain decisions.
8. AI-Based Customer Segmentation
To enhance personalized marketing, we developed a customer segmentation engine using unsupervised learning (KMeans, DBSCAN, hierarchical clustering) and RFM scoring. Customers were grouped based on demographic, geographic, behavioral, and psychographic data. Targeted campaigns based on these clusters led to a 7% increase in sales.
9. AI-Based Supplier Scoring
Procurement efficiency was improved through an AI-based supplier scoring system that evaluates vendors using performance metrics, delivery records, and quality scores. The system provides dynamic scoring and ranking, allowing procurement teams to select the most reliable and cost-effective partners.
10. Cstomer Specific Chatbot
We designed a smart chatbot for Boyner, one of Turkey’s leading retail brands. The chatbot assists customers with product recommendations, order tracking, and FAQs using natural language understanding. It enhances customer engagement and automates support for high-traffic online shopping periods.
