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C-Suite Challenge and ABWN Exit


The C-Suite Challenge - Program Ending Soon

In early 2017 Jigsaw Security decided to make our sensor product available as part of what we call the C-Suite Challenge. The challenge is to install our DNS server and sensor on your network and if we don't detect malware in the first 30 days you don't pay. To date we have had 2 companies take us up on the offer and both are now paying customers. By letting customers try our technologies before they buy it, we can show the value that will be realized. Both companies had malware active on their networks and didn't know it. Once customer was utilizing Dell SecureWorks for their threat intelligence and the other was using Fireeye appliances. Both were surprised when we brought them the positive findings. Not only did they not know they were infected but they also were leaking data to the threat actors.

We will be extending this offer for US based companies until 1 March, 2018. Let us show you the value of our solutions in a no obligation trial, you'll thank us.

Image: Uptick in undetected activity at one of our trial customers.

Our ABWN Exit (Financial):

Over the past month we have recognized over 128% increase in holdings of ABWN (Airborne Wireless Network) nearly doubling our availability to working capital in a single month. This end of the year boost was nice and to think that our intelligence platform provided the information used to make the pick. We were able to exit all positions between $2.80 and $2.64 per share. It took our stock broker several minutes to unload all of our positions. We believe that this company has real long term potential but this trade was modeled after activity that we had observed with this stock previously.

This goes to show that the Jigsaw Analytic Platform can be used for a variety of uses to include legal, document processing, stock and market trading, analysis of network and computer forensics data and much more. With the ability to process billions of data points in under a second, we can effectively make real world decisions based on what is happening in near real time.

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