Netskope AI Labs

Deep industry expertise

We have a team of dedicated ML scientists, security researchers, and product engineers who have track records of solving security and fraud problems in different domains with over 100 patents. Leveraging our expertise in AI/ML and security, we are developing large-scale AI/ML solutions for SSE. For example, we are integrating the latest AI/ML technology into our data security and threat protection features, as well as business operations.

AI/ML
use cases

Compliance and privacy

Enterprise security

Cloud DevOps

Network Optimization

Compliance and privacy

We have found AI/ML to be quite valuable when it comes to helping organizations comply with industry and governmental regulations such as GDPR, CCPA, PCI, and HIPAA. For example:

By applying deep learning techniques and analyzing traffic flows, we are able to detect sensitive information found in documents, images, and applications
Through the use of embedded user and entity behavior analytics (UEBA), we have trained models to discern normal behavior patterns versus those that originate from malicious insiders, compromised accounts, brute force attacks, and data exfiltration attacks.

Enterprise security

AI/ML has useful application in protecting enterprise assets from being compromised and weaponized for malicious activities including data exfiltration, botnets, spam, and so on.

Leveraging ML models we are able to complement and enhance the malware detection capabilities found in traditional anti-virus signatures, threat intelligence, heuristics, and sandboxes
Through language models, we have improved and sped up the categorization and detection of malware web domains, URLs, and web content.

Cloud DevOps

Netskope uses AI/ML to proactively monitor our cloud production environment to ensure the efficient and effective delivery of secure access service edge (SASE) capabilities.

Having led the industry in the classification of SaaS and web services for many years, Netskope now leverages AI/ML to speed up this work and maintain our edge
Netskope Operations takes advantage of AI/ML methods to prioritize incident management, troubleshoot, and stay ahead of production challenges before they occur.

Network Optimization

Network optimization requires vast amounts of data about network activity, application use, and application performance. AI/ML helps optimize access and performance in a number of ways, including:

Delivery of enterprise-wide predictive insights making it easier for network engineers to ensure higher network performance
Production of flow analytics on application performance throughout the entire network
Beyond ML-based fault insights, use AI to troubleshoot devices at the branch level

Commitment of responsibility

Our Commitment to the Responsible Use of AI

As a leader in the transformation of network, cloud, and data security, we are committed to the responsible use of artificial intelligence and machine learning. We will work with peers, academia, thought leaders, and governments alike to safely direct AI/ML efforts in a way that will benefit and not cause harm to our customers, partners, employees, and their families. We will take precautions and maintain a posture of transparency in our efforts.

Responsible AI Policy