Deep Instinct Prevention Platform

Deep Instinct is a preemptive data security company that applies deep learning—the most advanced form of artificial intelligence—to cybersecurity. The company developed DSX (Data Security X), the world's first and only purpose-built deep learning cybersecurity framework, which prevents zero-day threats and unknown malware with >99% accuracy and a <0.1% false positive rate in <20 milliseconds—750x faster than the fastest ransomware can encrypt. Deep Instinct is the pioneer in applying end-to-end deep learning to cybersecurity, fundamentally shifting the industry from reactive "assume breach" detection to proactive, prevention-first security.

Founded in 2015 in Tel Aviv, Israel by Guy Caspi, Dr. Eli David, and Nadav Maman, Deep Instinct is headquartered in New York City with R&D operations in Tel Aviv. The company has raised $322M in funding from investors including PayPal Ventures, BlackRock, NVIDIA, and Millennium Technology Value Partners. In September 2022, Lane Bess (former CEO of Palo Alto Networks and COO of Zscaler) became CEO, bringing over 35 years of cybersecurity experience to lead the company's growth.

Deep Instinct DSX Platform consists of two core components: DSX Brain—a proprietary discriminative neural network trained on tens of billions of data points over a decade—and DIANNA (Deep Instinct's Artificial Neural Network Assistant)—a GenAI-powered threat explainability engine. DSX Brain provides pre-execution prevention by analyzing files before they execute, stopping known and unknown threats including zero-day attacks, ransomware, and APT attacks. DIANNA complements prevention with expert-level malware analysis in <10 seconds. The platform protects endpoints (Windows, macOS, Linux, Chrome OS), servers, mobile devices (iOS, Android), cloud storage (Amazon S3, Amazon FSx NetApp), NAS environments (Dell CAVA, NetApp Vscan), and applications through agentless scanning, eliminating the need for cloud lookups and requiring only 1-2 updates per year compared to daily updates required by traditional solutions.