Business Overview
2014
284
-0.7%
$309M
7
14
0.6 years
Deep Instinct is the first company to apply deep learning to cybersecurity. Deep learning is inspired by the brain’s ability to learn. Once a brain learns to identify an object, its identification becomes second nature. Similarly, as Deep Instinct’s artificial brain learns to detect any type of cyber threat, its prediction capabilities become instinctive. As a result, zero-day and APT attacks are detected and prevented in real-time with unmatched accuracy. Deep Instinct brings a completely new approach to cybersecurity that is proactive and predictive. Deep Instinct provides comprehensive defense that is designed to protect against the most evasive unknown malware in real-time, across an organization’s endpoints, servers, and mobile devices. Deep learning’s capabilities of identifying malware from any data source results in comprehensive protection on any device, any platform, and operating system.
Employee Count
-0.7%
-3.4%
-6.7%
-12.9%
Employee counts updated on a monthly basis.
Lists
News
| ㅤTitle | Date | |
|---|---|---|
 | ㅤHow FraudGPT presages the future of weaponized AI | Venturebeat | August 14, 2023 |
Stock Chart
Founders (3)
| ㅤName | Title | Contact | |
|---|---|---|---|
 | ㅤEli David | CTO | |
 | ㅤGuy Caspi | CEO | 1 |
 | ㅤNadav Maman |
Board and Advisors (0)
Funding Rounds (7)
$309M
| Round | Date | Capital Raised | Investors | ||
|---|---|---|---|---|---|
 | ㅤDeep Instinct | Funding Round | 2023 | 1 | |
| ㅤDeep Instinct | Pre-IPO | 2022 | $62M | 2 |
| ㅤDeep Instinct | Series D | 2021 | $67M | 1 |
| ㅤDeep Instinct | Series D | 2021 | $100M | 7 |
| ㅤDeep Instinct | Series C | 2020 | $43M | 5 |
| ㅤDeep Instinct | Series B | 2017 | $32M | 4 |
| ㅤDeep Instinct | Series A | 2014 | $5M |
M&A Events (0)
Investors (15)
| ㅤInvestor Name | Investor Type | AUM ($) | |
|---|---|---|---|
 | ㅤAnne Wojcicki | Angel | |
 | ㅤATW Partners | Private Equity | |
 | ㅤBlackRock | Investment Firm | |
 | ㅤCoatue Management | Venture Capital | $21B |
 | ㅤColumbus Nova Technology Partners | Investment Firm | |
 | ㅤJ-Ventures | Venture Capital | $30.79M |
 | ㅤLG Technology Ventures | Corporate Venture Capital | $400M |
 | ㅤMillennium New Horizons | Venture Capital | |
 | ㅤNvidia | Corporate Venture Capital | |
 | ㅤPayPal Ventures | Corporate Venture Capital | $850M |
| ㅤShravin Mittal | Angel | |
 | ㅤThe Tudor Group | Investment Firm | |
| ㅤUnbound | Venture Capital | |
 | ㅤUntitled Investments | Venture Capital | |
 | ㅤZeev Ventures | Venture Capital | $1.65B |
Patents (3)
| Patent Title | Status |
|---|---|
| Methods and systems for malware detection | Granted |
| Methods and systems for detecting malicious webpages | Application |
| Methods and systems for data traffic analysis | Granted |
Research Publications (0)
Certifications (0)
AI Technology Stack
5
Using deep learning, we are able to identify even the slightest mutations and evasion techniques, thus detect and prevent Zero-Days and APT in real-time. Deep Instinct’s solution is based on a two- phase approach, similar to way that the brain learns and then acts in an instinctive mode: • Training phase: The training process is performed with hundreds of millions of malicious and legitimate files that takes place at Deep Instinct’s headquarters. The output of this process is the prediction model. • Prediction phase: Once a device has the deep learning prediction model (D-Brain), it becomes an autonomous analysis entity, allowing it to predict in real-time malicious intents and prevent them at a pre-execution level. There is no need for any supplementary analysis in a remote server or sandboxing appliance. The entire analysis and the determination of whether it is malicious or benign is done on the device within milliseconds.
Jobs (0)
