Today, we’re excited to announce a strategic investment from In-Q-Tel (IQT), which will help propel our industry-leading video analytics into the national security market.
We started Vintra with a mission to create the safest and smartest environments through automation and AI. We have had the privilege of pursuing this mission with some of the most forward-thinking security leaders in the Fortune 500, higher education, local government, and healthcare markets, enabling them to take a more proactive security stance. We’re excited to partner with IQT on new, mission-critical use cases for the national security market.
George Hoyem (Managing Partner, IQT), who will be working with us, said, “Deriving insights and actionable intelligence from large volumes of real-time cameras or archived video is a perennial challenge for the Intelligence and National Security community. Vintra’s novel application of machine learning to video understanding, combining purpose-built training data sets and proprietary convolutional neural networks that exploit transfer learning methodologies, is state of the art and will benefit our partners.”
Since our founding, we’ve focused on delivering three value propositions to our customers and partners and are now excited to bring these to the National Security markets. First, we provide a Total Environment Solution. Rather than deploying many analytic vendors with incompatible metadata structures, national security users can now deploy a single, compute-efficient solution from Vintra — force-multiplying and accelerating their analytic and decision-making capabilities that involve video data. Second, as opposed to costly rip and replace camera or VMS upgrades, we work with existing video infrastructure via an easy to deploy appliance or cloud solution that runs on any existing IP camera network, whether it is fixed or mobile, live or archived. Put simply, while we endeavor to be a single destination for our customers, we don’t return the favor and lock them up to expensive, inflexible architectures. Lastly, we’ll continue to focus on building a trusted solution, which is critical for national security users. This means building our own training data sets with real and synthetic data and developing unique neural network architectures from the ground up so we can explain performance and control improvement. It also means we rigorously focus on reducing bias as well as publishing and contributing to the wider computer vision community where our research can be helpful and spur more innovation.
We now live in a world where 3.3 trillion hours per day of video data are captured. Most of it is never reviewed because it has low value and it is hard to do. But, as we see on a regular basis in the pursuit of our mission, there are times when security situations change and the stakes become very high for individuals, organizations, and communities. We are excited to partner with IQT and accelerate the important work of building and deploying novel machine learning technologies to proactively and efficiently identify those critical segments of video that often hold the key to solving crimes and keeping people safe.