The technology can position itself in the vision AI market with 3 main strengths: 

1) Boost productivity, faster development frees up time for other projects.

2) Save costs, project costs drop in proportion to savings in development time.

3) Accelerating development progress, processing an AI model is possible with less code and lightens the engineering workload.

The platform can also provide the optimal trade-off among multiple features of the performance (e.g., latency, inference speed, model size, HW specification, etc.)

The required infrastructure can be minimized from servers and clouds to edge devices for model inference. It can be a good offer as a cost-saving alternative, and also a new suggestion for locations with bad or zero internet connection.

Not only the solutions mentioned above, but the biggest strength is also the ability that can expand the solution portfolio with internal R&D capability. Since the company has been established, they have an internal research team, which is separated from the development team. It helps improve the model optimization methodology and support more customers with different requirements at the same time. 

Currently, the company has also other solutions focusing on securing the safety of a massive number of people at the stadium by fall, fire, and related object detection.

The platform will enable Edge AI which has the benefit: 

A.      Faster Processing (Real-time, reducing latency and allowing for faster decision-making).

B.      Reduced Bandwidth Requirements (Since edge AI processes data locally, it reduces the amount of data that needs to be transmitted to the cloud, reducing bandwidth requirements and associated costs).

C.      Improved Privacy and Security: Edge AI can help protect sensitive data by keeping it local and limiting exposure to potential cyber-attacks.

D.   Increased Reliability: Edge AI can operate even when network connectivity is poor or unavailable, reducing the risk of system downtime and improving overall reliability.

    E.   Cost-Effective: Edge AI can be more cost-effective compared to cloud-based AI because it reduces the     need for expensive hardware and infrastructure required for cloud-based processing.

The Company’s core technology is AI model optimization, and they have developed a platform that anyone can accelerate their AI development.

This platform is a development pipeline that enables developers to build, optimize and deploy vision AI models faster and better. It typically takes 6-12 weeks using conventional tools to select, train, optimize, and deploy a vision DNN(Deep Neural Network). It makes developers can create and deploy high-performance models at the edge in three days.

The platform uses neural architecture search to find the best model for your application and hardware quickly, then trains the model in a hardware-aware manner to customize accuracy and latency for your processor. Then it applies model compression and acceleration to make your model small and fast without sacrificing accuracy. Finally, their platform generates executable code and packages it in a form that can easily be integrated into your application. While developers optimize model accuracy and latency, It can minimizes the time and money required to build these models. So far, AI models developed through their platform are commercially deployed on more than 45K devices.

The company has been developing vertical solutions using this platform for mobility and the smart city sector.

• For the mobility market, DMS, a driver monitoring system, can monitor the driver's behaviors as safety assistance.
• For smart city solutions, their model can analyze the traffic flow in intersections and crossings. It can detect and classify various traffic classes (e.g. trucks, buses, special-purpose vehicles, and pedestrians).

The use cases above are already commercialized in the market based on the platform and their expertise in model optimization. As a software and professional engineering provider, it is key to partner with other companies that can complement each other's limitations and secure general scalability.

Not only the cases above, they’ve also developed other AI applications in multiple industries e.g. safety & surveillance, office personnel management etc. As their platform is not limited to specific domains, they believe there is a strong motivation for developing edge AI in other markets. One of the main domains they’re considering is the smart factory or smart farm sector, as there is a big potential of digitalization and edge AI. So it’d be great to find a partner who can talk about potential collaborations in this category.

- Type of partner sought

Companies, public institutions, and private institutions which deal with power supplies

- Specific area of activity of the partner 

AI related entities are interested in Computer vision AI with efficiency or model improvement regarding the inference speed, detection performance, and reducing latency.

According to the customer’s current status, they can support building a new model or improving the existing model by customizing the platform parameter.