Tame fragmented data with QuikFynd advanced data search using the Intel® Distribution of OpenVINO™ toolkit to radically improve data organization and searchability
Data can be counted among the most valuable assets of our time. It comes in all shapes and sizes, and it is constantly growing. It must be stored, and it must be protected, at no small expense. As any business grows, the mountain of data grows with it, becoming increasingly cumbersome to manage in an efficient way. Cloud solutions, while helpful for storing files, also means there are more places where any given file could be stored. For those without photographic memories, recalling the last-known location, or even the exact name of a file can pose a challenge. How many hours a week are wasted searching multiple locations and guessing at file names? How many files are just out of reach because they were misnamed or misfiled? Human attempts at organization are subject to human error. Artificial Intelligence could be the answer.
Harnessing the power of the Open Visual Inference and Neural Network Optimization (OpenVINO™) toolkit, QuikFynd radically improves data organization and searchability.
“Using the OpenVINO™ toolkit gave us radically improved neural network performance on a variety of Intel® processors. It really helped us to uncover a cost-effective solution and almost real-time performance of our application.” —Vikas Aditya, CEO, QuikFynd
Using advanced algorithms coupled with machine learning, QuikFynd delivers a powerful tool for organizing, searching, and sharing data. In a small to medium-sized enterprise, QuikFynd is deployed as a VM or in the cloud, and can simultaneously search multiple file servers as well as all associated cloud drives. QuikFynd can also be deployed as an app, with a responsive design that works on mobile devices or laptops, allowing users to search and access data across cloud drives and on network-attached storage (NAS) from anywhere. After an initial indexing of your drives, QuikFynd quickly scans and extracts text from documents, PDFs, and PowerPoint* decks, so files can be searched for by keywords even if the filename has been long forgotten. The software finds and even highlights matching text in context, making it easy to choose the correct file and to find related files at a glance, eliminating the need to open and close multiple files to find the right one. Images can be searched just as easily, with intelligent AI-based algorithms that can identify and tag common objects in pictures, from mountains and rivers to the family dog.
Figure 1. Image tags in QuikFynd.
Figure 2. QuikFynd on a desktop.
Figure 3. QuikFynd on a laptop.
Figure 4. QuikFynd on multiple devices.
While QuikFynd easily travels between servers and cloud drives, your information does not. All data remains in its respective storage account, while a single result screen compiles potential matches and displays where the files are housed. All data and the search index always remain on the customer’s device to ensure privacy and security for the user. For secure sharing with others, QuikFynd can create and store a temporary collection of chosen items in the cloud. This collection can be password-protected and the associated link can be given an expiration date or simply deleted at any time.
Over time, searching and organizing with QuikFynd will become further streamlined. The QuikFynd auto-tagging function can identify documents by topic as well as find names of people or organizations and places mentioned. This allows for even more potential paths for searching, depending on a given user’s needs. QuikFynd also notes where multiple copies of a single document are kept, even across multiple cloud drives. Users can eliminate redundancies and storage space is freed up by removing unnecessary duplicates.
QuikFynd employs Intel® Deep Learning Boost (Intel® DL Boost) technology through the OpenVINO™ toolkit on 10th generation Intel® Core™ processors. By making full use of multiple cores and multiple threads, QuikFynd can run advanced, deep searches through terabytes of data in multiple locations at breakneck speeds.
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