Go figure: living in the information age means we're all dealing with a lot of information. Whether we're on-boarding new employees, brainstorming with colleagues or engaging with partners, every one of us is interacting with gigabytes of data on a daily basis. And its impact on how we work together is just beginning to be figured out.
All of this innovation is triggering an explosion of rich content — images, video, audio — which, in all their unstructured glory, are incredibly hard to manage and organize. As a result, some companies are left spending millions to manually identify, classify and tag these files, and every user is stuck wasting time on mundane tasks instead of meaningful work. And the real shame is, despite all the work you're doing, there's a huge amount of value inside your content that's still out of reach.
Today, we're changing that. Starting with your images.
Images are the second most common and fastest growing content type in Box. Businesses of all sizes rely on massive libraries of images, including product photos for online catalogs, customer-submitted images for claims and loan applications, completed forms captured via mobile phone, images of structures to assess quality or maintenance issues, and much more.
To help unlock the value of these images to your business, we're excited to introduce image recognition with Box. We're applying machine learning to images, making it even easier for companies to discover, organize and drive actionable insights from their content.
Now, upon uploading images to Box, any objects and handwritten or typed text in images can be automatically detected and indexed as metadata, bringing actionable context to your content. To power this, we're leveraging Google Cloud Vision, a state-of-the-art machine learning tool that automatically catalogues images into thousands of categories.
Image recognition is already revolutionizing the way our beta customers manage their images simply and securely across their extended enterprise:
- A major media company is using image recognition to automatically tag massive amounts of inbound photos from freelance photographers around the globe. Previously, there was no way they could tag every single image. Now they can automatically analyze more images than ever before, and unlock new ways to use these images in their company.
- A retail customer is using image recognition to optimize digital asset management of product photos. With automatic object detection and metadata labels, they can cut out manual tagging and organization of critical images that are central to multi-channel processes.
- A global real estate firm is leveraging optical character recognition (OCR) to digitize workflows for paper-based leases and agreements, allowing their employees to skip a manual tagging process while classifying sensitive assets more quickly.
The cloud content management use cases keep multiplying. Our beta customers are already unlocking more value from their images as they accelerate detection of quality control issues, streamline hiring and on-boarding, improve data collection and processing, and much more.
This is just the beginning. Our goal is to bring you new ways to work faster and smarter with machine learning, making your content most valuable in Box. We're excited to see how customers use these new capabilities to answer questions about their content they didn't know to ask, create more amazing experiences for their own customers, and ultimately move their businesses forward.
Want to learn about our private beta for image recognition? Box customers on an Enterprise plan can sign up here.
We also invite you to join us at BoxWorks 2017, our annual user conference happening October 10-12 at Moscone Center in San Francisco. To register and view the full agenda, click below: