Trueface.ai: Revolutionizing Face Recognition with Intelligent Solutions

Trueface.ai: Revolutionizing Face Recognition with Intelligent Solutions
Written By:
Ashish Sukhadeve
Published on

The modern technological applications are getting smarter every day with the use of artificial intelligence (AI). Face recognition is one such technology which has embraced AI successfully to increase the quality of our lives. Face recognition is capable of serving a broad spectrum of applications across industries. It is one of the most powerful technologies featured in digital identification and verification tools.

As our identities continue to digitize, we need methods and solutions to protect and authenticate them. Passwords are simply too easy to hack and biometrics have been the necessary solution for the last ten years. Pairing face recognition with social or behavioral information certainly makes it more difficult to comprise an identity. A company which stands as a promising player in the field of face recognition and is significantly helping enterprises increase safety and security for their customers is Trueface.ai.

Trueface.ai provides face recognition and digital identity solutions. The company's offerings include a cloud-based API and on-premise solution for customers with varying data/privacy needs.  Trueface.ai platform has been deployed across multiple industries for verifying digital identities for KYC worldwide and safety/identification in public environments.

Trueface.ai's vision has always been to make face recognition more secure and easier to use. In working towards that vision, the company developed tools that prevent spoof attempts as well as unique components that allow developers to build facial recognition UIs and simplify integrations.  Trueface.ai started researching face recognition in 2012, launched an intelligent doorbell with face recognition in 2014 and pivoted in 2016 to provide physical access control solutions. Trueface.ai spun out of an access control company. Today, Trueface.ai continues to see a huge demand for their face recognition software and the unique capabilities it offers.

Brain Behind Trueface.ai

Shaun Moore is the Co-founder & CEO of Trueface.ai. He has been building startups since 2009 with his current Co-founder and CTO, Nezare Chafni. Their experience in hardware since 2013 has helped them to shape their face recognition offerings. Shaun is very active in the international entrepreneurial community and speaks at events across the world on building start-ups and the future of face recognition. Moore is a thought leader and has written highly informative articles about the industry in leading publications.

Understanding Patterns Through Deep Learning

Trueface.ai recognizes that the layers of machine learning are continuing to be peeled back. There is a significant risk to machine learning now called adversarial attacks. These are mechanisms which plague algorithms. The company is focused on understanding all of the risks associated with machine's learning ability to recognize patterns and how these patterns can be thrown off. "I think deep learning very much involves a human element because the systems are only as intelligent as we can architect. We need to actively understand the limitations of what we create and continue to pursue all of the positives and negatives associated with our creations", says Moore. "Specifically, for face recognition, our technology is only as powerful as our architecture, thought process and training sets. The solutions we are building today are the experiences we will have in five years. So artificial intelligence and the data output is extremely important".

Cutting-Edge Services Recognized by the Industry

The founders' history in hardware has given Trueface.ai the resources to build proprietary spoof detection technology. The company has partnered with major multinationals in the security, travel and hospitality, and fintech industries and are exploring the real estate space now. Trueface.ai's technology can retrofit existing hardware so the clients do not need to purchase new cameras. The company has been able to innovate their architecture to support older systems, making the face recognition platform usable across a variety of industries from embarking on ships to identifying customers as they enter a bank.

Trueface.ai graduated from 500 start-ups in San Francisco. It was accepted into Nvidia's Inception Program. Mashable and TechCrunch covered the company's launch. Trueface.ai was named as one of the top 10 companies helping to shape the future of IoT.

Key Strengths that Helped Overcome Challenges

On the challenges faced, Moore says "Competing with the likes of Amazon, Microsoft and Google is never an easy hurdle but by offering easier to configure products, more specialized solutions, and stronger technology, we are able to demonstrate higher quality solutions. Building custom hardware was a very different path to take but it helped us showcase how our technology could be used in access control and lead us to where we are today, focusing on face recognition software and the solutions we can power".

Future Industry Predictions

Moore believes we are still very much at the stage of understanding how impactful technologies can be. Artificial intelligence and face recognition have been around for 40+ years but with the recent advancements in processing power, we are witnessing the true value now.

The facial recognition landscape is rapidly changing. Significant advancements in processing power, edge computing, 3D technology, and machine learning are leading to the democratization and commoditization of facial recognition software. They are also leading to increased efforts from larger enterprises to adopt this technology at a rapid pace, even if they don't recognize the immediate need.

As we glance into the future of our infrastructure, cameras have become omnipresent. Their inevitable upgrade cycle will incorporate facial recognition technology to combat fraud and personalize experiences. This technology will spread due to the increased scalability of software architectures, advances in 3D technology, and the advent of edge GPUs. The result of edge face recognition will be convenience and bespoke experiences in our personal lives thereby bringing more efficiency to our workforce and building safer communities.

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