Nightfall AI vs Zscaler DLP

A side-by-side comparison on deployment model, data residency, licensing basis and security coverage. Structural facts are verifiable against vendor documentation; the scored dimensions are our assessment.

NF

Nightfall AI

Nightfall AI

6.8

Average across eight dimensions

Deployment
SaaS only
Licensing
Per user or API volume
Time to value
Fast
Segment
SMB / mid-market
G2
ZS

Zscaler DLP

Zscaler

7.0

Average across eight dimensions

Deployment
SaaS only
Licensing
Per user, per tier
Time to value
Medium
Segment
Enterprise
G2

Score by dimension

Dimension NF ZS
Data residency control 2 2.5
Pricing value 6.5 5
Detection accuracy 8 8
Response speed 7.5 8.5
Ease of setup 8.5 7.5
Management UX 8 8
Integration depth 7.5 8.5
Security coverage 6.5 8

Nightfall AI

  • +Machine learning classification performs well on unstructured content
  • +API-first design makes it straightforward to embed in custom applications
  • +Fast to connect to common SaaS tools without agents
  • SaaS only — content is sent to Nightfall for inspection
  • Endpoint and network channel coverage is minimal; this is SaaS-focused

Best for Engineering-led teams protecting data inside SaaS and custom applications

Watch out Not a replacement for endpoint or network DLP — scope it accordingly

Zscaler DLP

  • +Inline enforcement at internet scale with minimal latency impact
  • +Natural fit where Zscaler already handles web and private access
  • +Exact data match and indexed document matching are available at higher tiers
  • SaaS only, with inspection performed in Zscaler's cloud
  • Value depends heavily on already routing traffic through the Zscaler platform

Best for Enterprises already standardised on Zscaler for secure access

Watch out Standalone value is limited — this is a platform module rather than a product

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Other comparisons

Data last verified 2026-09-16. nPro publishes this comparison. Where nPro appears as one of the platforms listed, its card is marked and its scores are our own assessment. Third-party review scores are sourced from public vendor profiles. Structural facts — deployment model, licensing basis, residency — are verifiable against each vendor's documentation.

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