Vognition: Making Devices ‘Smarter’ through NLP

As IoT ecosystems continue to grow, their penetration into the masses paves the way for ‘smart’ homes and buildings. Yet, staying connected does not necessarily translate to smartness. The ‘human experience’ is also a crucial variable in the equation for ‘smart devices.’ Voice recognition, the novel feature that many phones and speakers boast about is indeed a huge leap toward appending the ‘smart’ tag on devices. After all, listening is an indispensable trait of a ‘smart being,’ and to that end, Natural Language Processing (NLP) has become the must-have entity for any business that holds stakes in the making of the ‘smart’ world. For, the technology has the potential to even replace ‘touch’ as the primary medium for interfacing with gadgets. On the other hand, for device manufacturers, as more voice portals come into existence, the cost associated with developing and implementing cross-compatibility in NLP interfaces will increase. This is where Oakland-based, Vognition grabs the spotlight. “We are a one-stop solution for IoT manufacturers to imbibe natural language voice control into their products,” says Michael V Liguori, the founder and CEO of Vognition.

For instance, a garage door or a thermostat powered by Vognition can be fully equipped to receive voice commands from users and execute actions accordingly. Additionally, Vognition provides APIs and SDKs that help customers to integrate their applications with other voice portals, be it through mobile applications, Amazon Echo, or Google Home, glasses, wall plates, cars, or even motorcycle helmets. As a matter of fact, Liguori’s initial vision as the founder of Vognition was to come up with an NLP solution ecosystem. However, it was after the launch of Apple’s Siri—about two weeks after Vognition patented its technology—that he realized how the technology could prove to be indispensable in delivering a non-siloed, unified experience to the end-consumers. The company thus plays a crucial role for IoT manufacturers in quickly aligning their offerings in tune to that of the end consumer’s smart-home expectations. Vognition has also ensured that their ecosystem is well protected and reliable from a security and privacy standpoint.

And that’s not all! Vognition goes the extra mile to analyze customer usage patterns to understand how they interact with devices.

We are a one-stop solution for IoT manufacturers to imbibe natural language voice control into their products

In addition to helping Vognition in enhancing their SaaS-based NLP functionalities, Vognition’s clients can leverage the insights to fine-tune their devices to match intrinsic customer expectations. “We did a consumer trial with our first major client for voice locks and thermostats, and we saw from the data that people often wanted to control the garage door as well. Upon developing a garage door command, it was discovered that around twenty percent of the voice commands were targeted at garage doors,” recalls Liguori.

Nexia Home, a division of Ingersoll Rand has partnered with Vognition to bring about a smart makeover in their housing projects. Their residents can now have command over indoor and outdoor cameras, pool PH-meters, automated blinds, and even water valves. Since their humble beginnings in 2015, Vognition has powered more than 100,000 homes with devices that can be easily rendered ‘voice compatible’ via any smart appliance that bears a built-in microphone. Vognition recently acquired a $700,000 grant from Highlander Angel Network (HAN), a highly sought-fund of the New Jersey Institute of Technology (NJIT).

With a great headstart propelled by its novel technology, Vognition is well positioned to take on the smart-housing sector by storm. The company plans to focus on expanding its reach through sales and marketing, at the same time, maintain a healthy dedication to customer service.


Oakland, NJ

Michael V Liguori, Founder & CEO

The Company’s NLP powered SaaS offering helps IoT manufacturers to render their devices with voice compatibility