LONDON--(BUSINESS WIRE)--Deep Instinct, the first and only cybersecurity company to apply end-to-end deep learning to predict, identify, and prevent cyberattacks, is continuing its strategic expansion into EMEA, contracting with T-Systems (Poland), one of the region's largest IT services providers, to utilize and distribute Deep Instinct’s protection to its customers. Deep Instinct also signed strategic partnership agreements with Cyber Monks and Spinnakar to distribute Deep Instinct’s deep learning-based solution across the region.
Leading Deep Instincts’ EMEA expansion is Brooks Wallace, VP Sales EMEA, a veteran cybersecurity sales leader with over 20 years of experience in building sales teams. Wallace will oversee the newly opened sales and support office in the UK and forge additional strategic partnerships with MSSPs across the region.
“Our expansion into EMEA comes at a critical time for the region, and contracting with T-Systems Poland attests to the unique value of our deep learning-based cyber-attack prevention solution,” said Guy Caspi, CEO and Co-founder of Deep Instinct. “We look forward to working with our partners in the region and enabling enterprises to shift from an ‘assume-breach’ approach to preventing both known and unknown attacks in real-time.”
“As cloud adoption and managed security services become more prevalent, our strategic partnerships with Cyber Monks and Spinnakar will enable us to protect and serve more clients throughout the EMEA region,” continued Brooks Wallace, VP of Sales, EMEA, at Deep Instinct.
As part of the new strategic partnerships, UK-based Spinnakar and Germany-based Cyber Monks will distribute Deep Instinct’s solutions across the UK and DACH (Germany, Austria, and Switzerland) respectively. As major distributors within their regions, both companies partnered with Deep Instinct having recognized the product’s added resilience to prevent more threats, compared to other solutions. This is a critical factor as they work towards further enabling their growth strategies in the coming years.
“With the surge in malware attacks targeting vulnerable endpoints, the need for a solution that provides autonomous prevention with minimal false positives is critical”, said Stefan Stefaniak, Cyber Security Advisory Team Leader for T-Systems Poland, which in addition to using Deep Instinct’s solutions will be providing it to customers as well. “The functionality that Deep Instinct provides is best-in-class, leveraging deep learning to achieve unmatched accuracy and speed anywhere in an enterprise ecosystem, with multi-layered protection across all endpoints, networks, mobile devices, and operating systems.”
“In seeking a new technology partner with an innovative solution to further differentiate our value to clients, Deep Instinct stood out among the rest with their proven prevention capabilities,” said Anas Handous, CEO of CyberMonks. “Partnering with Deep Instinct has allowed us to combine our expertise with their capabilities, enabling us to solve our customer's most critical cybersecurity issues.”
“As cybersecurity costs for enterprises have risen drastically with an accelerated threat landscape, providing solutions that respect budgetary concerns has become a priority,” said Gerard Brophy, Managing Director of Spinnakar. “Partnering with Deep Instinct enables us to provide a reduced total cost of ownership, with an autonomous prevention solution that drives down detection and remediation costs and a lightweight footprint that does not require constant connectivity to provide protection.”
About Deep Instinct:
Deep Instinct is the first and only company to apply end-to-end deep learning to cybersecurity. Unlike detection and response-based solutions, which wait for the attack before reacting, Deep Instinct’s solution works preemptively. By taking a preventative approach, files and vectors are automatically analyzed prior to execution, keeping customers protected in zero time. This is critical in a threat landscape, where real-time is too late. To learn more visit https://www.deepinstinct.com/