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9/29/2014 | 2:43:09 PM
1. The behavioral standard deviation of the application in the context of the organization using it.
This will continue to be useful because applications in the contexts of their organizations have unique behavioral fingerprints, we will continue to build on these in collaboration with the app vendors themselves. Ideally these would be metered via APIs, but today we supplement some of them through other vectors such as Identity and Access API's (provided by Okta or ADFS), and our SAML-based reverse proxy.
2. The realm of human capability.
This is the low hanging fruit that, as you astutely stated, will become largely commodotized over time and likely adopted by the SaaS vendors themselves as a value added component of their service, like 2FA and IP restrictions. Where we think we'll add value here is by having a broader dataset that encompasses users across several SaaS platforms.
3. The unique behavioral fingerprint of a user.
This is the big one, this is where we're investing 60% of our R&D, hiring the best machine learning engineers, and the brightest heuristic scientists. We believe this is where the competitive battle lines will be drawn.