Deep Instinct – Endpoint Protection
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Deep Instinct - Endpoint Protection
|Company (that provides the nominated product / solution / service)||Deep Instinct|
|Company size (employees)||100 to 499|
|Type of solution||Software|
In 3 bullets, summarize why this product or service is different from the competition and deserves recognition:
- Autonomously prevents more threats before they get the chance to execute. A critical factor towards maintaining a continuously trusted state.
- Incredibly low TCO. The many automated processes, combined with the bi-annuall updates, the lightweight agent with minimal footprint and CPU <150MB footprint & <1% CPU, and the focus on prevention make this product incredibly easy and inexpensive to operate.
-The sophistication of the deep learning algorithm produces a high level of detection accuracy, both in terms of correctly preventing malicious attacks from executing and in terms of reducing the rate of false alerts. The deep learning model achieves this because it conducts a more in-depth analysis of files where very little can get by inaccurately detected.
Deep Instinct is the first and only company to apply end-to-end deep learning to cybersecurity to provide organizations with resilient prevention against even the most advanced cyberattacks. Deep Instinct takes a critically different approach with its use of deep neural network algorithms, an advanced form of AI that has an instinctive ability to effectively prevent new malware no other software can detect.
Deep Instinct is able to predict and prevent a broad range of threats – known and unknown – anywhere in zero-time. Threats are prevented anywhere within the enterprise from any type of file-based or file-less cyberattack in groundbreaking time, with unmatched accuracy and speed. Every endpoint, server, mobile device, network and operating system is protected against the widest range of attacks. This advanced approach to threat prevention ensures that attacks are identified and blocked before any damage can be caused.
Unlike other solutions that degrade as new threat campaigns emerge, Deep Instinct’s deep learning-based solution remains resilient and it is this resilience that is critically needed and yet lacking by many organizations across industries today.
Deep Instinct has been uniquely able to prevent new malware threats, that at the time no other vendor was able to detect, let alone prevent. Such examples include Dharma ransomware (2018) MyLoBot (2018), ServHelper (2019), Formbook (2019), Snake ransomware (2020) RagnarLocker Ransomware (2020) and many more.
The TCO of deploying Deep Instinct is remarkably low as the product is designed to ease and reduce the security burden on analysts in the later stages of the cybersecurity lifecycle. Due to the predictive nature of the deep learning algorithm updates are required only bi-annually, the majority of malware is prevented in the pre-execution stage, so analysts often times don’t even know they’ve been targeted, many manual processes are automated and the agent is incredibly lightweight.