COMPANY PROFILE 2017 - VUNO Inc.

1 2017 COMPANY PROFILEWe believe that AI can be of great value to doctors. VUNO products will not only provide improved workflow but a whole new user VUNOOur TechnologyKey Offerings010203 Contents45 COMPANY PROFILECOMPANY PROFILEVUNO | | VUNO VUNOA bout VUNOWe are quickly approaching an era where AI has taken over the world. The medical field is certainly not an exception, with its various problems being solved and improved by the help of AI. Based on the vast majority of data collected, some AI-based models perform and imitate similarly as, if not better than, humans. However, we believe that the core value that AI brings to the table is not just about its accuracy, that far exceeds human abilities. Through AI, we can provide tools that are ready to be used at any moment to improve your workflow with tools that it has never seen before. Acknowledging that AI has reached almost every aspect of our life, we pursue affordable products that you can comfortably choose from.

2 After all, it is the true needs of doctors that we take into careful consideration when we create solutions for problems that AI can take on. We believe that AI can be of great value to doctors. VUNO products will not only provide improved workflow but a whole new user experience. 67 COMPANY PROFILECOMPANY PROFILEVUNO | | VUNO VUNO-MED The VUNO-MED series will foster a work environment for medical staff that will help expedite the decision-making process with better accuracy. Based on data collected from a number of videos and signals from various medical fields, we have come up with ways to provide diagnostic assistant services. The VUNO-MED series is a collective collaboration of doctors and engineers with years of experience in medical data analysis, as well as those with various medical experiences. From X-ray features and CT scans to a biosignal monitoring system, the series provides a variety of services such as quantifying and assisting with diagnosis of diseases, as well as analyzing data.

3 With the VUNO-MED series powered by VUNO, you can experience the future of VUNOOur ExpertiseExpert experience and knowledge in medical innovations We have radiologists and medical scientists as advisory members on board with us, with an in-depth collaboration and cooperation of data analysis specialists and UI/UX designers working on our products. Established in 2014, we have reached more than 10 major hospitals in Korea, as we continue to develop ideas on numerous possibilities made through the process of codevelopment, clinical trials, and verification. We have the experience and a philosophy on how technology can provide the needs of hospitals and doctor. We have issued 14 patent applications on the topic of innovative technology and presented more than 10 international clinical trials with Service Corporation International (SCI). Currently, we are in the process of getting a variety of medical devices with AI-based diagnostic software (CADx/CADe) licensed.

4 We have participated in establishing guidelines for licensing AI-based medical devices. Currently, we are in the process of implementing advice from the Ministry of Science and Technology, Food and Drug Administration, and Federal Emergency Management technology to support the entire cycle of analyzing various forms of medical data We have secured our very own deep-learning engine (VUNO NET) as well as our own data collecting and analyzing platform (VUNO-MED ). By using these, we have analyzed various data and diseases and invented different models through learning. From data collection, preprocessing, reevaluation/relabeling to optimization of the deep learning network, we have the software and infrastructure to support the full process, which has been validated through multiple clinical and development of products that are ready to launch in the market Having completed the entire pre-process prerequisite for doctors to use in real time (strategizing/ collecting data/developing/clinical trials/licensure), we have the experience and expertise of not only conducting but managing on our own.

5 We bring AI-based products to life as a real, legitimate medical equipment for our customers. Our specialization lies in proactive, transparent communication with our customers and clients to best understand and solve any potential problems that they may experience. With the VUNO- MED series, you get to decide how to pursue the results that you VUNO89 COMPANY PROFILECOMPANY PROFILEVUNO | | VUNO History2014201620152017 Since the foundation of VUNO in December 2014,We are moving ahead to innovate artificial of VUNOSeed investment and inducement( USD 1million, Bonangels/futureplay/TIPS)Establishment of Research Institute (Korea Industrial Technology Association)Development contract on AI-based diagnostic devices, signed and sealed with 4 regional hospitals in major citiesDevelopment contract on AI-based diagnostic devices, signed and sealed with 8 hospital in major citiesCompletion of VUNO NET the Deep-learning enginePresentation of academic journal and thesis at RSNA, C-MIMI, AJR, JDI, A investment and inducement ( USD 3million, SBI Investment, Smilegate Investment, HB Investment )

6 Selected as one of the top 5 for ImageNet ILSVRC 2015 Classification TaskCompletion of VUNO-MED Bone Age development and in process of clinical trials (Ministry of Food and Drug Safety)Participation and presentation at NvidiaGTC/SIIM/RSNA ExhibitionsKGMP Certified (Ministry of Food and Drug Safety; response to ISO13485)Participation and presentation at Nvidia GTC/RSNA Exhibitions PartnersBackersAbout VUNOA bout VUNO1011 COMPANY PROFILECOMPANY PROFILEVUNO | | VUNO Deep Learning Engine VUNO NETOur TechnologyAlthough deep-learning models show impressive performances, there are many things to consider when commercializing products. For example, a number of algorithms require extensive computing resources which can be problematic for a commercialized product. Invented in 2015, VUNO NET the deep-learning engine based on CNN/LSTM, is one of many that we have developed utilizing the most up to date network architecture and processing technique.

7 VUNO NET is compatible with any software/hardware environment, and we can guarantee the fastest in the lightest form. In addition, VUNO NET has been evaluated over many years by over a 100 different architectures on GPU machines like Titan X or engine exclusively for analyzing medical data1213 COMPANY PROFILECOMPANY PROFILEVUNO | | VUNO Data Collection &Labeling Modules1 Medical Image Processing Modules2 Deep Learning Applications3 Web-based Labeling ToolDeep LearningFrameworkDeep LearningPrimitive LibraryLanguage & Math LibraryVUNO NETC++CPUnVIDIA GPUsCUDAAPI ServerDatabaseLabeled ImageCPUGPUsWebGLcuDNNO perating System (Linux/Windows)cuFFTcuBLASOpenBLASATLASM KLBLASP latform for medical data collection and model development, VUNO-MED Based on medical data, the initial process of data collection with model development and its optimization is crucial to solve any given problem that may surface. Built on cloud-based data, VUNO is an exclusive platform that supports optimization through data collection/relabeling and model learning.

8 We provide the best environment for the application of deep learning in medicine, where many of the collected image data may require reviewing and relabeling from a experts. We understand how costly the entire process ofmonitoring and reevaluating data can be. Therefore, we would like to provide you the best environment to make this process easier and more efficient. Compatible with Linux, Windows, and OS, VUNO-MED is the final product and piece of invaluable experiments, trials, and reviews conducted by various expert organizations and officials. Our technology Future Human AI MBCOur platform includes data acquisition and labeling toolsOptimized algorithms made from experience and deep understanding in medical dataWe have profound understanding of deep-learning and machine-learning technology. We have also designed an independent architecture that can produce a top-notch performance against any given problem.

9 In 2016, we were selected as one of the top 5 competitors at the world s biggest, ImageNet s own ImageNet Large Scale Visual Recognition Competition (ILSVRC). Through major news networks, we were introduced as the deep-learning COMPANY worth collaborating with more than 10 major hospitals and collecting more than millions of visualdata from X-ray/CT/MRI scans, we have developed various deep-learning models to analyze,classify, detect, and quantify data, which has led to commercialization of a variety of diagnosticsoftware devices. The following explains what separates our products from others from a technological viewpoint:The strongest yet lightest module By utilizing our VUNO NET engine, we can embed any shape of medical device, including computing conditions with insufficient resources, and provide services where any device can of variance between institutions/image settingsAlgorithms developed based on a deep understanding of each X-ray/CT machine s unique visualcharacteristic allows us to provide a universal performance for images from any equipment in any algorithms for various labeling In the process of data labeling with a large number of experts, we inevitably run into a differencein opinions, which then usually leads to following the majority.

10 However, we see the difference ofopinions as another way to produce meaningful information from doctors with different, diverseexperiences of , medical image-specialized module We provide modules for quantification/detection/classification/ search essential for medical imageanalysis, as well as commercialization-qualified services for algorithms and specific diseases. Each module has gone through both verified clinical trials and oriented UI/UXWe produce optimal UI/UX designs that considers the actual clinical working environment and thehospital s system. In the end, we believe that even the best technology is useless without a gooduser technology1415 COMPANY PROFILECOMPANY PROFILEVUNO | | VUNO Based on deep-learning models, VUNO has developed products derived from various medical image dataas well as medical image analysis and diagnosis. The innovative results that we have suggested have beenpresented in the highest academic journals and institutions in different fields.