About CyberSmart
Technology
CyberSmart Technology has discovered that there is a wide disparity between the user’s expectation and the AI-compatible mechanism; which is what the company is set to bridge. According to our studies, current facial recognition (FR) tech is built on “face foreword photos”. Lighting, angle, and obstructions such as glasses, hair, or masks cause inaccuracies.
Our Vision: To enhance customers’ experience by utilizing computer vision and smart facial recognition using AI-powered facial recognition technology.
Our Mission:
To revolutionize the present facial recognition market by developing high-quality, innovative smart facial recognition technology that is safer and more effective for people across the world.
Problems
Current facial recognition (FR) tech is still limited. FR is built on “face foreword photos”. Lighting, angle, and obstructions such as glasses, hair, or masks cause inaccuracies. Right now, with the Covid crisis, face masks are prevalent, so this is causing a major challenge to current FR AI.
Currently, accuracy rates remain a problem given the massive amount of input data required to make systems usable in real-life contexts, like airports. The more accurate the AI, the fewer errors. However, when moved up to a large scale with millions of data points, there is a greater chance of errors coming in and reducing the accuracy rate.
Currently, accuracy rates remain a problem given the massive amount of input data required to make systems usable in real-life contexts, like airports. The more accurate the AI, the fewer errors. However, when moved up to a large scale with millions of data points, there is a greater chance of errors coming in and reducing the accuracy rate.
Lastly, existing FR AI cannot be used for object tracking. And this is the next big step if FR tech is going to move into mainstream retail use.
Solutions
In the model, the company provides Facial Recognition AI with an expanded accuracy range for angles, lighting conditions, and obstructive objects. Up to 45 degrees lateral, 30 degrees vertical, and partially obstructed still have 90% accuracy.
The company’s algorithm is extremely accurate for identification and tracking in controlled areas including Airports, Offices, and Prisons. It also can be used as traditional FR tech for security/login. The company has a highly accurate and secure system with an optimized response time in very high transactions
The company’s algorithm is extremely accurate for identification and tracking in controlled areas including Airports, Offices, and Prisons. It also can be used as traditional FR tech for security/login. The company has a highly accurate and secure system with an optimized response time in very high transactions
However, the platform and algorithm have shown an appropriate efficiency in object tracking such as car tracking in parking lots and highways. Object tracking AI combines geo-positioning, bio-informatics, and FR tech.
Level 1: Advanced FR
Level 2:Liveness detection
Level 3:Action detection
Our Product Demo Videos
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Our Team
Danish Ahmed Ansari
CEO
He is a dedicated sales leader with 15+ years of success in growing revenue through the development of high-impact sales and business development plans, especially in the consumer goods domain. He had worked as Senior Sales and Marketing Manager, Consultant and CEO. As Chief Executive Officer of CyberSmart Technology, Mr. Ansari aims to utilize his excellent years of experience in the industry to bring the company to the Canadian market, expected to be a thriving and profitable business.
Rajnessh Kant Saxena
CTO
He is a performance-driven professional with 23 years of rich combined expertise in development, database management, ERP & managing IT operations. He had worked as Senior Developer, Assistant Manager, Systems and Data Processing Manager. As Chief Technical Officer of CyberSmart Technology, Mr. Saxena builds workflow and processes to ensure the success of teamwork and use the shortest path to achieve the target making him a strong asset for CyberSmart Technology ensuring the tech advantage for it in the Canadian market.
Murugan Krishnasamy
CFO
He is an intelligent professional with 22+ years of experience in operations and project management covering cards, loans, account opening and payments in consumer and corporate banking. He had worked as Credit Operations Officer, Manager in card operations, Assistant VP, Vice President, Head of the Card Centre, ATM services and central cash operations. As Chief Financial Officer of CyberSmart Technology, Mr. Krishnasamy will be an instrumental resource in the company’s financial growth initiatives, especially in their calculated move into the Canadian face recognition market.
Rajeev Yadav
CMO
He is a result-oriented businessman with 25+ years of experience. He had worked as Production Manager, Sales, Marketing & Operation Manager and Project Operation Manager. As Chief Marketing Officer of CyberSmart Technology, Mr. Yadav’s in-depth knowledge in areas of strategic marketing and people relations will be vital for its ability to thrive in Canada.
Frequently Asked Questions
Answer:
Facial Recognition Technology (FRT)Face foreword photos Accuracy
Training the AI models at high volumes
Object tracking
Answer:
Securing enough budget to carry out all the marketing activity soundly.Providing ROI for marketing activities.
Brand awareness for clients to adopt solutions.
Answer:
Capture the attention of target audiences by providing a secure, and cost-effective FRT solution for companies.Facilitating brand awareness through promising and quality service, excellent customer service, and marketing.
A clear roadmap to approach the market.
Identifying the target audience, and understanding the values held by those most likely to engage with the service, thereby instilling brand loyalty in customers.
Answer:
Direct Sale to private technology vendors, security companies, and law enforcement agencies across Canada.Answer:
Official website, Digital advertising, SEO, etc.Our Blogs
Proactive Steps for Business Leaders in Ensuring Cybersecurity and Protecting Sensitive Data
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