Today we announced our Intelligent Defense Platform. In so doing, we believe we have released the first defense platform that is built for the new reality of cyber: post-Mythos. As many have pointed out, the rise of AI use by attackers means we have to assume a vastly more intelligent attacker able to massively scale the scope and duration of their attacks. If you'd like to learn more about our perspective on post-Mythos cyber, please grab the whitepaper from our web site: www.deeptempo.ai. Our perspective shares a lot with that of organizations like Carnegie Mellon, and many others including NIST, the UK's cyber center, and even yesterday's Executive Order on AI and cyber security.
Let me introduce you to our Intelligent Defense Platform.
First, our Intelligent Defense Platform uses AI to counter AI. Unlike most solutions in the AI SOC today, we built our own model from the ground up. BNY and other design partners helped us to build a solution that we are confident today is state of the art in identifying especially novel attacks. These days novel attacks are becoming quite common. So our LogLM is the right solution at the right time, especially for MSSPs and larger customers in finance, telecommunications, government, critical infrastructure, technology and healthcare. The LogLM plugs into your existing environment, runs very well in your on prem environment or on the cloud, and saves you money by reducing false positives while dramatically increasing user confidence that they are seeing even increasingly common advanced attacks.
In the post-Mythos world, an easy to use, cost effective, efficiency increasing overwatch is more important than ever.
Yesterday's article by Dr. David Bray and former FBI leader Jeff Frazier puts this in broader perspective: this OODA Loop analysis.
Secondly, DeepTempo's Intelligent Defense Platform now includes support for our Vigil open source AI SOC project. Vigil has fast become the leading open source AI SOC. In some ways I started building Vigil over ten years ago, when, along with an amazing team of cofounders, I started and led StackStorm. StackStorm was the first open source "event driven automation" project, and eventually became the leading open source SOAR as well as the scalable workflow engine behind complex devops actions at Netflix, Webex, Meta and elsewhere.
Fast forward to today and I'm again chasing that autonomic dream, but this time we see on prem and cloud hosted reasoning models are able, with a bit of help from Vigil, to close the loop and learn from their activities to burn themselves into your environment. Please note that you don't have to use our Vigil. You can use your own existing AI SOC. And while many point to our shift left detections and response platform as a way to save money, especially when deployed with Cribl and Snowflake, the approach also drives up the ROI of your SIEM, including Splunk, while driving down the needless anxiety and churn of false positive storms.
Last but not least, and actually most importantly, the Intelligent Defense Platform includes a learning loop. This loop includes the ability to measure the efficacy of detections today and is being extended to measure the efficacy of end to end workflows as well. We built the measurement of detection and now workflow (such as Vigil) efficacy for our own work in building AI models and systems, and we quickly recognized that this loop can be used by our customers as well.
My thinking about what is needed has evolved as we've grown closer to major users. That said, the overall vision remains. We set out a few years ago to reexamine cyber root and branch with the prospect of AI powered attacks on the horizon. Now that this future is a reality, we are releasing Phase II of our vision for DeepTempo's reinvention of cyber from first principles.
AI native approaches to anticipate, see, isolate and respond to especially advanced attacks are now crucial for every organization, and even for the protection of open societies themselves. Unlike prior SaaS solutions, the IDP runs in your environment. Unlike prior ML solutions for seeing novel attacks, the IDP is proven to produce very low false positives with very little or even no adaptation required. Finally, the entire solution is built with transparency as a central ethos: transparency of potential costs when you use Vigil, transparency of confidence in our advanced detections, and transparency of detections end to end whether the included LogLM or other ML detections are relied upon.
As always, free trials are available. Take it out for a test drive. Recently we completed a side by side versus one of the great internet companies' own detections. Without any adaptation we showed .08% false positives. That shocked them (and me a little bit). It promises to change what they can do in cyber, and now in conjunction with their threat intel we are helping them to shift very far left. What about you? Will you trust a start-up like DeepTempo? How about a founder who has been helping global enterprises succeed in technology adoption across 5 start-ups and more than 25 years? DeepTempo is already making a lot of early fans and advisors look very intelligent indeed. Please get in touch if you are interested in collaborating to dramatically improve your security systems.
