Veritone Acquires Machine Box, Extending Its Capabilities with New Building Blocks for Rapid Development of Artificial Intelligence Solutions
Acquisition adds a suite of powerful yet easy-to-use cognitive engines across multiple AI categories, for developers to customize, train and build upon as a toolkit within aiWARE
Veritone Inc. (NASDAQ: VERI), the creator of the world’s first operating system for artificial intelligence, aiWARE™, today announced its acquisition of Machine Box, Inc., a developer of state-of-the-art machine learning technologies that give organizations a suite of simple yet robust tools and models to create customized AI engines that can be deployed to enhance new or existing business solutions. Machine Box provides an elegant reference architecture across multiple cognitive categories, including face and object recognition, text analytics, data classification and personalized recommendation. This intuitive toolkit provides developers a guide to design and deploy (on-premise or in the cloud) tailored AI engines. When coupled with the Veritone AI operating system, developers, systems integrators and end customers will be able to produce bespoke, end-to-end AI-informed solutions for their specific use cases that can be deployed anywhere, accommodating for security and regulatory compliance requirements.
A recent Gartner, Inc. report predicted that by 2022, one-third of application development projects will leverage hosted AI services, with fewer than 5% of those application developers building their own AI models. Another Gartner report outlined some of the challenges CIOs face in implementing home-grown, AI-based solutions, including the difficulty of acquiring all-encompassing internal skills to construct algorithms and train models, and to “monitor, maintain and govern the [AI] environment.” The combination of Machine Box’s proven tools with the flexibility and ease-of-use of Veritone’s aiWARE operating system will address these key barriers, making it easier for users to deploy configurable, future-proof solutions.
Chad Steelberg, Veritone’s Founder & CEO said, “A founding principle of Veritone’s philosophy and technology has been democratized, robust and platform-agnostic AI capabilities. Veritone’s unique AI operating system, ecosystem of hundreds of cognitive engines and intuitive set of applications have been a major step forward in making AI solutions accessible to a greater number of people and organizations than ever before. This acquisition is another major step on that path – Machine Box’s AI toolkit, which fits perfectly with Veritone’s portable architecture and standards, will allow technology-savvy individuals to quickly and easily train any number of cognitive engines to create custom models deployable where they need them to enhance their business offerings.”
Machine Box CEO Aaron Edell said, “We are very excited to be joining forces with Veritone – their global reach and established presence as a trusted AI software provider and standards setter, combined with Machine Box’s easy-to-use AI toolkit, will enable users to progress quickly from a standing start to sophisticated use of artificial intelligence. This will further democratize AI capabilities, and we believe that it will also go a long way toward establishing company-agnostic standards for AI technology.”
The Machine Box toolkits will be made available as a part of the Veritone Developer application environment for existing and new accounts to leverage. To get started, sign up for a free account for Veritone Developer today at veritone.com/devsignup. To learn more about Machine Box, subscribe to the Machine Box blog at blog.machinebox.io/.
The consideration paid by Veritone in the acquisition was $2.0 million, plus an earn-out of up to $3.0 million based on the achievement of certain milestones. Such consideration is comprised of a combination of Veritone shares and cash.
About Machine Box
Machine Box combines state-of-the-art Machine Learning technology with a first-class developer experience, and delivers it all inside Docker containers, making it the easiest way for developers to build and deploy artificial intelligence into their applications both in the cloud and on premises. Machine Box addresses a range of artificial intelligence use cases including facial detection and recognition, image and text classification, natural language processing, content recommendation and more.
Safe Harbor Statement
This news release contains forward-looking statements, including without limitation statements regarding the Gartner forecasts relating to application development projects, the expected integration of Machine Box’s products with aiWARE and the expected benefits to customers. Without limiting the generality of the foregoing, words such as “may,” “will,” “expect,” “believe,” “anticipate,” “intend,” “could,” “estimate” or “continue” or the negative or other variations thereof or comparable terminology are intended to identify forward-looking statements. In addition, any statements that refer to expectations, projections or other characterizations of future events or circumstances are forward-looking statements. Assumptions relating to the foregoing involve judgments and risks with respect to various matters which are difficult or impossible to predict accurately and many of which are beyond the control of Veritone. Certain of such judgments and risks are discussed in Veritone’s SEC filings. Although Veritone believes that the assumptions underlying the forward-looking statements are reasonable, any of the assumptions could prove inaccurate and, therefore, there can be no assurance that the results contemplated in forward-looking statements will be realized. In light of the significant uncertainties inherent in the forward-looking information included herein, the inclusion of such information should not be regarded as a representation by Veritone or any other person that their objectives or plans will be achieved. Veritone undertakes no obligation to revise the forward-looking statements contained herein to reflect events or circumstances after the date hereof or to reflect the occurrence of unanticipated events.