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Wald alternatives & similar sites

Wald: AI Data Loss Prevention (AI DLP) and Secure LLM Access for Enterprises — 18 websites ranked by shared content topics, category and on-page relevance.

Each result shows its full tech stack, contacts and AI-policy — not just a name · Browse all sites in Artificial Intelligence →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
nightfall.ai ↗	70 match shared topic	Nightfall: AI Data Security & Data Loss Prevention Platform	en	information-and-network-security	robotsllmsaihumans	emailphone	none
ipswitch.com ↗	65 match shared topic	Transfer Data the Secure & Compliant Way \| Progress	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
dualitytech.com ↗	65 match shared topic	Secure Data Collaboration for Regulated Industries \| Duality	en	information-and-network-security WordPress	robots llmsaihumans	emailphone	none
cyera.com ↗	65 match shared topic	AI Security Platform \| Protect Data & Secure AI \| Cyera	en	artificial-intelligence	robots llmsaihumans	emailphone	none
okta.com ↗	60 match shared topic	Secure Identity for Employees, Customers, and AI \| Okta	en	information-and-network-security Adobe Experience Manager	robotsllmsaihumans	emailphone	none
auth0.com ↗	60 match shared topic	Secure AI Agent & User Authentication \| Auth0	United States~ en	artificial-intelligence	robots llmsaihumans	emailphone	none
snyk.io ↗	60 match shared topic	Snyk AI Security Fabric \| Secure Code, Models & Agents \| Snyk	en	information-and-network-security	robotsllmsaihumans	emailphone	none
forcepoint.com ↗	60 match shared topic	Forcepoint: The #1 AI Data Security Platform	en	information-and-network-security Drupal	robotsllmsaihumans	emailphone	none
accessdata.com ↗	60 match shared topic	Exterro \| AI-Powered Data Risk Management Platform	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
varonis.com ↗	60 match shared topic	Varonis \| Leader in Data and AI Security. For Cloud, SaaS and On-Prem	en	information-and-network-security HubSpot	robotsllmsaihumans	emailphone	none
avepoint.com ↗	60 match shared topic	AI-Ready Data Security & Governance for Enterprise \| AvePoint	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
snyk.co ↗	60 match shared topic	Snyk AI Security Fabric \| Secure Code, Models & Agents \| Snyk	Colombia en	information-and-network-security	robotsllmsaihumans	emailphone	none
hoop.dev ↗	60 match shared topic	hoop.dev \| Accelerate your AI agents. One gateway to every data source.	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
relyance.ai ↗	60 match shared topic	AI data security platform	United States~ en	information-and-network-security	robotsllmsaihumans	emailphone	none
dataminr.com ↗	60 match shared topic	AI-Powered Real-Time Event, Threat & Risk Intelligence - Dataminr	en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
alice.io ↗	60 match shared topic	Alice \| Secure, Safe, & Trustworthy AI	en	information-and-network-security	robots llmsaihumans	emailphone	none
bigid.com ↗	60 match shared topic	BigID: Enterprise Data Security Platform for DSPM & AI	Israel~ en	information-and-network-security WordPress	robots llmsaihumans	emailphone	none
aembit.io ↗	60 match shared topic	Aembit \| Agentic AI and Workload Identity & Access Management	en	information-and-network-security WordPress Lightspeed	robots llmsaihumans	emailphone	none

How the match score works

Each match is a 0–100 similarity score — the higher it is, the more two sites resemble one another. It’s computed automatically from our own crawl data (never from what a site says about itself) by combining several independent signals, so a high score means several of them point the same way:

shared topics how many of the same fine‑grained content topics (IAB sub‑categories) both sites cover — the main signal.
same category whether they sit in the same business / industry category.
content & title how closely their titles and page descriptions line up in wording and meaning.

No single signal decides the result — they’re blended together. Treat the score as a way to rank candidates rather than an absolute percentage; the chips on each result show which signals contributed.