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Customers

AutoEdge's products have served multiple customers from a wide array of applications. We help our customers use their current big data innovatively to create more reliable products and better serve their clients.

Manufacturing Company

The manufacturing industry is under constant pressure to detect defects as soon as possible in their production process. Defects in manufacturing that go undetected become more and more expensive as they advance in the manufacturing line. An error becomes the costliest when a defective product is sold to end consumers.

AutoEdge helps manufacturers quickly detect defects and provide clear actional items to fix inefficiencies.

10

Data samples required to build a comprehensive synthetic dataset

3-steps

to go from raw data to real-time monitoring

10 hrs

Warning before reaching production failure

Edge IoT

DNNs are powerful image-processing tools, but their deployment on edge devices is challenging due to limited computational resources and memory. A new solution from AutoEdge integrates DNN inference with a camera and an LCD display for image acquisition and detection exhibition, respectively.

300 KB

Total DNN model memory

91.9 ms

Inference time

1.845 mJ

Energy consumption

HVAC Company

Given its end-to-end, automated, and interpretable characteristics, AutoEdge significantly simplifies the development and deployment of AIoT-enabled remote anomaly identification while allowing domain experts to quickly understand the issues of HVAC systems. These characteristics translate to benefits, including identifying energy savings opportunities, extending asset life, minimizing repair costs, and reducing emissions.

1,000

Units analyzed simultaneously

30%+

Energy savings from preventive maintenance

25%

Fewer emissions

Oil and gas company

Given the sensor log of the oil drilling station, AutoEdge provided the attribute and physical meaning of individual variables. Specifically, with the physical attributes of the monitored values, AutoEdgre provided a typical value range and the causal relationship between variables, e.g., when pressure increases, the temperature will increase afterward.

48 hr

Warning provided before breakdown

10,000+

Outliers detect with no human intervention

24

Unique variables monitored and correlated

Video Analytics (sports)

AutoEdge leverages the power of computer vision systems by using activity tracking technologies to further the emergence of a new era in sports analytics. Our team has used player-tracking variables and game statistics to gather more data and provide relevant information about players' performance

2.5 hrs

Of video analyzed per second

1:1 score

Developed a talent-similarity score

100

Players analyzed