1,000 Box Skills and counting!
Box Developers created more than 1,000 Box Skills since our GA
Box Skills enhance content in Box using powerful AI services. Whether you want to extract information from documents with natural language processing, label objects in images, or transcribe audio using speech-to-text technologies, Box Skills help you get more value out of your content in Box.
Today, we’re excited to share that more than 1,000 Box Skills have been created since our GA announcement just a few weeks ago, enhancing more than 1,000,000 files in Box with AI. Our developer community, made up of our enterprise customers, services partners, technology partners and many others, is using the Skills framework to unlock new types of value from content and use Box’s Cloud Content Management services in completely new ways.
Here are some of our favorite ways developers are using Box Skills to improve the way their business works with content:
- Streamline contract review cycles — use OCR and natural language understanding to extract key provisions from contracts, M&A due diligence documents, and leases to better organize and streamline the review process. Any information extracted from these documents is applied as metadata on the file in Box, which is indexed for search and can be used to trigger workflows and retention policies as necessary.
- Accelerate the onboarding experience — use computer vision, OCR and natural language understanding to recognize different onboarding documents, such as tax documents or benefits forms, and extract any inputs as structured data. All of the information extracted from the onboarding documents is written as metadata on the file in Box and can be used to trigger workflows to prompt additional information from new employees (as needed) or be sent directly to a CRM or HRIS system via the Box metadata API.
- Make digital assets more searchable — many marketing teams store large libraries of marketing images, audio and videos in Box. Using technologies like computer vision, speech-to-text, and video intelligence, digital assets can be recognized and labeled based on the contents of the assets, such as photos of a particular product. All of the asset tags are written to the files as metadata, which is indexed in Box’s search functionality. With this rich tagging, end users can search for assets based on topics and terms familiar to them, instead of remembering specific file names or folder locations.
There are tons of potential use cases for applying AI to content in Box to improve productivity, accelerate cycle times, or reduce risk. To get some ideas, you can explore sample Box Skills in our Box Skills project directory or jump right into creating your own Box Skill using our developer documentation.
Have you built a Box Skill that you want to showcase on this blog? Send us an email at firstname.lastname@example.org with the subject line “Box Skills Story Submission — YOUR COMPANY NAME.” A member of our team will reach out if your story is a good fit!
We can’t wait to see what you build!