As much as software companies might wish that workers did all of their work in one suite of software applications, the reality is much different. People don't even confine all of their work-related activities to one machine, much less one vendor's suite of applications. As a result, file discovery -- from conversations that take place in workspaces like Slack to articles saved in Evernote to email attachments sent via Outlook to files uploaded to a shared Dropbox account -- can be a time-consuming process. Currently, it relies on a worker remembering where they stashed something and a variety of application and operating system search tools.
"We've transitioned to a world where, as you're working as an employee, files can become scattered across many many places. So you have files on your company server, files in the cloud, and all these applications like Salesforce, email or Slack," said Aaron Ganek, CEO of Cloudtenna.
Cloudtenna aims to change that. Its cloud-based DirectSearch service offers file discovery services for corporate data by using machine learning to index the files, their metadata and their user activity, then offer intelligent search options to users.
Ganek says there are three core problems with having files siloed in separate systems: for users, search is a time suck; if neither users nor IT admins know where files are, then they don't know exactly how secure those files are; and if those files present security risks, then the IT department opens itself and the larger organization up to significant liabilities.
"What we do is we catalog file activity across disparate data silos and provide machine learning to mitigate the chaos," he said.
Cloudtenna indexes files for any application or cloud-based service the IT administration has connected to Cloudtenna -- for example, a company might OK Salesforce and Sharepoint both being connected to Cloudtenna, or a user might choose to connect Evernote, Salesforce and Outlook. It also logs metadata, like what the file name is, the application it originated with or is stored in. Each file's contents are indexed. And finally, Cloudtenna logs activity associated with the file -- who last opened it, when it was last opened, when it was last modified, when and how it was shared, and with whom it was shared. In the case of logging file-sharing activities, that information is constrained by the security restrictions individual applications and services put on files and specific users.
The net result for Cloudtenna users is that they have access to a file discovery tool on their desktop which will let them search for files by content, by activity or by a user.
And Cloudtenna's intelligent search engine offers predictive results based on past user patterns. So if a specific user is often looking for files shared by a specific colleague, the search box might auto-suggest the colleague and update results.
The company is planning to expand its product line to help organizations maintain compliance with regulations, something that offers fresh urgency in a post-GDPR world.
"If you start to think about all this information we're collecting, what we're able to do in the future is great audit and governance capabilities," Ganek said. A potential future capability, courtesy of the machine learning at the core of the product, would be the ability to alert IT administrators if a user is exhibiting atypical behavior based on their past file activity or search history. Those alerts could be used to detect breaches.
Cloudtenna's DirectSearch will be commercially available in July. Interested parties can request to join a beta.
