Nightfall AI
vs. Google Cloud DLP

Supports 5 use cases: Data Detection and Response, Data Security Posture Management, Data Exfiltration Prevention, Data Encryption, and Data Discovery and Classification

Secures the entire Google Workspace environment, from Gmail to Google Drive

Supports data detection and response, but not additional use cases such as data exfiltration prevention, data encryption, etc.

Disjointed, unintuitive DLP capabilities

Broad DLP coverage of business-critical SaaS applications, including Slack, Jira, Confluence, Zendesk, Salesforce, GitHub, and more

Unified workflow across SaaS apps and email

Data encryption with employee opt-in, along with several robust administrative controls like setting expiration dates and blocking email forwarding

Protects Google Workspace only

Separate workflows for Google Drive and Gmail

Encryption with no employee opt-in; lack of administrative controls in Gmail

Leverages state-of-the-art neural networks and fine-tuned LLMs in detecting PII, PCI, PHI, passwords, API keys, and intellectual property with high precision and recall, ensuring minimal noise and fewer missed detections

Detects sensitive data in 50+ file types, including docs, images, spreadsheets, HTML, PDFs, logs, images, and zip archives

Leverages columnar information in spreadsheets and CSVs for improved accuracy

Utilizes a sophisticated combination of PII and medical entity detection models, enhanced with GenAI, to accurately detect PHI and minimize noisy alerts

33% lower precision and 60% lower recall in detecting PII, PCI, PHI, and credentials, leading to an overwhelming number of false positives and missed detection

No support for embedded images or zip archives

No special handling for spreadsheets or CSVs, resulting in increased noise

No dedicated PHI detector; provides a limited set of standalone PII and health entity detectors, and lacks combination logic and GenAI validation, leading to unreliable detection

Effortless setup, intuitive triage, seamless remediation, and comprehensive reporting

Customizable detectors, detection rules, and policies

Intelligent policy engine with the ability to define policies according to users, user groups, drives, file permissions and more

Steep learning curve

Lack of customizable policy options

Limited support for different types of detectors

Flexible remediation options include automated, manual, and employee remediation (with Human Firewall)

Human Firewall feature offers employee self-remediation options as well as coaching to automate incident response and maintain a secure-by-design culture

Seamless integration with leading SIEM and SOAR tools (e.g. Azure Sentinel and Splunk) via webhooks and REST APIs

Customizable, real-time alerting for admins and employees via Slack, Jira, webhooks, and email

Option for employees report false positives and provide business justifications for sharing sensitive data, leading to improved model fit and reduced noise

Manual admin-only remediation

No employee self-remediation options

No webhooks or APIs to automate DLP incident triage and response

No flexibility to send alerts to non-Google Workspace platforms

No option for employees to report false positives or business justifications