Headquartered in Atlanta, Georgia, Unscrambl was founded with the vision of helping organizations take the best possible decisions given the most up-to-date knowledge about the current state of the world and how it will respond to the actions. While Big Data has been instrumental in helping organizations gain a better understanding of their world, not many organizations have been able to successfully translate that understanding to optimal actions that can drive their business objectives.

This failure to easily harness Big Data, to drive actionable insights and to execute actions in a changing world in real-time spurred the Unscrambl team to come up with a better approach. There were a few key realizations. The first is that analytics and actions had to be industry and use-case specific to allow easy adoption and execution. The second is that real-time matters: the quicker you are to act, the quicker you are to succeed, or fail. And the third is that the world is always changing, so we need to be able to observe the effect of our actions, continuously update our model of the world and continuously evolve our decisions and strategies.

With the help of these realizations, we have come up with a kit of solutions that can be implemented blazing fast so data-driven businesses would neither lose their competitive edge nor their customers and that are forever adapting and learning as the world changes.

All these solutions are powered by a real-time cognitive decisioning platform that utilizes stream analytics, machine learning and decision theory to tackle numerous use-cases across different industries. Specifically, we have come up with the concept of “Robots”, which are automated engines that can drive business outcomes by sensing the current state of the world, deciding and executing the best actions, observing the effects of the actions, and using the feedback to update their model of the world.


To derive meaning from focused real-time insights and spur action and automation in the world's leading industries.


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