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Gravitational alternatives & similar sites

Teleport: Unified Identity Securing Classic & AI Infrastructure | Teleport — 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 Information And Network Security →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
goteleport.com ↗	85 match shared topic	Teleport: Unified Identity Securing Classic & AI Infrastructure \| Teleport	United States~ en	information-and-network-security	robotsllmsaihumans	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
trstd.com ↗	60 match shared topic	#trstd – Know What's Real \| Trust Infrastructure for People, Businesses & AI	en	information-and-network-security HubSpot	robotsllmsaihumans	emailphone	none
yoti.com ↗	60 match shared topic	Building the world's trusted identity platform • Yoti	en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	partial · 8
vouched.id ↗	60 match shared topic	Vouched \| Digital Identity Verification	Indonesia en	artificial-intelligence HubSpot	robotsllmsaihumans	emailphone	none
signicat.com ↗	60 match shared topic	Identity solutions for a trusted digital world - Signicat	en	information-and-network-security	robotsllmsaihumans	emailphone	none
descope.com ↗	60 match shared topic	Descope \| Customer and Agentic Identity Platform	en	artificial-intelligence	robotsllmsaihumans	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
veriff.com ↗	60 match shared topic	Global AI Identity Verification & KYC Solutions - Veriff	en	information-and-network-security WordPress	robots llmsaihumans	emailphone	none
mlcves.com ↗	60 match shared topic	ML CVEs — CVE Tracker for ML & AI Infrastructure Risk	en	information-and-network-security	robots llmsaihumans	emailphone	none
daytona.io ↗	60 match shared topic	Daytona - Secure Infrastructure for Running AI-Generated Code	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
regulaforensics.com ↗	60 match shared topic	Identity Verification Solutions & Forensic Devices by Regula	en	information-and-network-security	robotsllmsaihumans	emailphone	none
saviynt.com ↗	60 match shared topic	Saviynt \| AI-Based Identity Security and Access Management Platform Solutions	en	information-and-network-security HubSpot	robotsllmsaihumans	emailphone	none
cynet.com ↗	60 match shared topic	Cynet Unified, AI-Powered Security Platform for MSPs & SMEs	en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
mend.io ↗	60 match shared topic	Mend.io \| Application Security and AI Security, Unified	United States~ en	information-and-network-security WordPress	robotsllmsaihumans	emailphone	none
thirdkey.ai ↗	60 match shared topic	ThirdKey.ai - Securing the Agentic Future	United States~ en	information-and-network-security	robots llmsaihumans	emailphone	none
agentpin.org ↗	60 match shared topic	AgentPin — Domain-anchored cryptographic identity for AI agents	en	information-and-network-security	robotsllmsaihumans	emailphone	none
socure.com ↗	60 match shared topic	The AI Platform for Identity & Risk Decisioning \| Socure	en	artificial-intelligence	robotsllmsaihumans	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.