Technology
Video is quickly becoming the richest resource on the Web and in the enterprise, not only through video sharing sites such as YouTube, but also through online services such as podcasts, streaming media, and video downloads provided by broadcasters such as the BBC’s iPlayer. The leaps in communication technologies are also facilitating tools such as video conferencing and personal mobile video telephony. As a result of these growing media sources, the expectation to be able to interact with, and access video will increase, and corporations of all types must be ready to deliver. With an upswing in information and video assets, tagging schemes and taxonomies are an increasingly popular method to index video according to keywords, categories, or production details. Such schemes fall short when attempting to process and search video files without due regard to their content. Autonomy maintains an open philosophy with regards to the techniques it uses within its solutions and is dedicated to selecting methods which optimize its technology’s performance, whether they are old or new. Accordingly, Autonomy embraces traditional or legacy search methods such as keyword, Boolean, parametric and others. However, it is perhaps best known for its pioneering work in conceptual search based on computational pattern recognition (nonlinear adaptive digital signal processing) and contextual linguistic analysis. IDOL 
At the heart of Autonomy’s advanced infrastructure software lies the Intelligent Data Operating Layer (IDOL). IDOL uses sophisticated pattern matching techniques and probabilistic modeling to form a conceptual and contextual understanding of all digital information - structured and unstructured - and thus enables computers to process information like humans do by reading, watching and listening to it. Through these advanced analytics, IDOL automates the processing of this content regardless of its format, location, language, or which application is associated with the data. Sophisticated mathematics is applied to derive meaning by determining dominant terms and idea distancing. IDOL sits above an organization’s myriad silos of data and acts as an information integration layer: performing keyword and conceptual search, speech analytics, video indexing, entity extraction and search, email and Instant Messaging (IM) search as well as more advanced processing of the information such as eduction, clustering and categorization. IDOL’s ability to extract meaning from information through an understanding of both the content and context of data allows Autonomy to enrich it based on knowledge already held within the organization. Through the automation of deep video indexing, speech recognition, automatic archiving, and retrieval, rich media assets are put into context with regards to other files. By applying advanced analytics users can harness the power of these associations through delivery of unprecedented access, visibility and management of their entire corpus of information. Automation 
Autonomy’s solutions remove an organization’s reliance on the human intervention typically required by most video processing applications. Autonomy offers a single IDOL platform for understanding and processing all digital information. Only IDOL can perform keyword and conceptual search, speech analytics, video search, email and IM search, and categorization - all on the same platform. Alternative approaches require stitching together different technologies with potentially conflicting formats and the associated ongoing running costs of having such a Frankenstein’s bride. Consequently, they compromise stability, pose maintenance issues and may necessitate excessive technical support along the upgrade path. IDOL, as a single platform, eschews these problems, and its superior benefits are realized without any concessions in performance as each component of IDOL is best of breed. By automating processes that were previously performed by costly and tedious labor, Autonomy’s technology offers a direct path to substantial bottom line savings. Cross-referencing of content is automatic as Autonomy’s infrastructure identifies related material within the operating layer and determines significant relationships between information using multi-tiered relevancy modeling. Processes such as hyperlinking, information clustering, alerting and categorization of content can all be precisely automated with any file or set of files.
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Autonomy Group Customers
