Adaptive Security for Adaptive Threats

What we do

Your central strategy for cybersecurity threats

Centralized Solution

Censtra complements existing infrastructures by centralizing all source intelligence, decision making and, when permitted, autonomous actions into a single solution

Strategically Focused

Censtra’s core technology applies Machine Learning and Game Theory to identify anomalous patterns throughout an organization’s infrastructure

Autonomous Operator

Censtra’s Cybersecurity Operator functions at wire speed to analyze, assess, learn, report, act upon and remediate any threats to its environment


Introducing CHESS

Designed for digitally intense, heterogeneous ecosystems requiring operations at wire speed to secure business, operational and IT systems

Collaborative and Cost-Effective

A Multi-functional Security OS that scales to accommodate added capabilities through REST API integration

Flexible Deployment Model

CHESS is a geo-scalable software appliance that can be deployed either on physical or virtual servers - On-Premises, Cloud or Hybrid

Open and Modular

Designed to balance computing speed & efficiency using either CPUs or GPUs and using a modular framework built on a hardened Linux OS with proprietary Machine Learning Algorithms


What does CHESS do?

CHESS is designed first and foremost to function as a non-human “operator on the network”. An operator’s core function is to analyze, assess, learn, report, act upon, and remediate issues and events that arise; that is what CHESS accomplishes, however automatically, at wire speed, and in a fully comprehensive manner.

Allowing autonomous actions realizes the CHESS platform’s fullest capability. CHESS uses a proprietary artificial intelligence capability referred to as a Matrix of AI Nodes™ to observe, detect and identify known and emerging threats and attacks.



Globally Aware

Every version of CHESS learns from events on its network and through subscriptions from global threat intelligence feeds.

Advanced Threat Detection

CHESS is able to detect common and difficult to identify attacks. Through the power of Machine Learning CHESS is able to distinguish real threats from false positives.

Machine Learning

CHESS uses a multi-dimensional matrix of AIs to analyze events from any OS, any device, mobile or fixed. CHESS builds a holistic situational awareness which is enterprise-wide. This allows CHESS to nimbly and intelligently respond to emerging cyber threats.


CHESS has been designed to use minimal resources and is built on a scaled down and hardened Linux Operating System.

Optimal Decision Making

CHESS can commit resources to protecting the critical areas on your network, exchange data and take action collaboratively with existing security resources.

Game Theory

When a threat is identified, CHESS Deep Learning AIs respond with a mitigation plan. This plan is executed in coordination with human operators. Progress is continually monitored and refined through move and counter-move. Feedback is then incorporated into the Deep Learning models.


Shamim Kabir

Shamim has a career that spans over 18 years in a variety of different industries, most notably Financial, Pharmaceuticals, Healthcare, and Cybersecurity. He has played key roles in both managing teams as CEO and also advising high-level execs and organizations on Information Security issues. His role as CEO has been to drive the development and deployment of machine learning and automation systems.
Shamim brings excellent business strategy and a deep understanding of Cybersecurity best practices. This combination of skills makes him an excellent leader and strategist for Censtra.

Tom Beauchamp-Arnold
Chief Information Officer

Tom has worked for key players in the computer industry for over 45 years: IBM, Digital Equipment, Oracle, Niksun, and now Censtra. He has shipped products at all levels of computer systems, including device microcode, networks, clusters, lock managers, operating systems, databases, and security applications. He had the great privilege of studying AI under pioneers Marvin Minsky, Patrick Winston, and Seymour Papert.

Terry Morgan
Chief Strategy Officer

Terry Morgan is a career US Marine with 30+ years global experience analyzing business, explaining technologies’ impacts, and developing strategies. During twelve years at Cisco and subsequently as a consultant, he advised governments, international organizations, standards bodies, think tanks, not-for-profits and companies including Fortune 500, start-ups, investment, and boutique consulting firms. This unique experience at the intersection of government, business and technology provide Censtra’s business and technology leadership unique insights for developing their technology and business.

Kory Beach
Research Scientist

Kory Beach is a theoretical physicist by training, specializing in advanced computational research. His strong understanding of high-level mathematics and complex theoretical models makes him a valuable member of the Censtra team. He is able to design new strategies, heuristics and mathematical techniques that will be used by CHESS to detect, remediate and prevent threats. Kory's unique ability to deconstruct complex ideas and seek inspiration from unlikely places helps Censtra to develop groundbreaking innovations in the Cybersecurity space.

Dean Brown
Software Engineer

Dean has over 35 years of experience developing award-winning software, using many different languages, platforms and technologies. He has worked in many different industries, including educational software, media companies, games, medical research software, and most recently cybersecurity with Sandstorm and NIKSUN. He has expertise in all aspects of software development - design, coding, algorithms, data structures, debugging, maintenance, UI design, usability.

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Censtra is currently a stealth mode company. For more information or for a CHESS demo, fill out the contact form below.

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