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Usecoverbase alternatives & similar sites

Coverbase - Agentic third-party risk and security — 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
joincoverbase.com ↗	100 match 2 shared topics	Coverbase - Agentic third-party risk and security	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
sargentic.com ↗	70 match 2 shared topics	SARGENTiC - Agentic Cybersecurity. On Duty.	HK~ en	information-and-network-security	robotsllmsaihumans	emailphone	none
cyber.airforce ↗	69 match 2 shared topics	SecurityPilot — Agentic GRC Intelligence	en	information-and-network-security Spree Commerce	robotsllmsaihumans	emailphone	partial · 8
sanwi.ai ↗	69 match 2 shared topics	Sanwi — The Knowledge and Security Layer for the Agentic Era	en	artificial-intelligence	robotsllmsaihumans	emailphone	partial · 8
saramonitoring.com ↗	69 match 2 shared topics	SARA Agentic AI for Security	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
defendblackkite.com ↗	68 match 2 shared topics	Black Kite \| Standards-Based Third-Party Cyber Risk Management	US~ en	information-and-network-security	robots llmsaihumans	emailphone	none
useblackkite.com ↗	68 match 2 shared topics	Black Kite \| Standards-Based Third-Party Cyber Risk Management	US~ en	information-and-network-security	robots llmsaihumans	emailphone	none
joinblackkite.com ↗	68 match 2 shared topics	Black Kite \| Standards-Based Third-Party Cyber Risk Management	US~ en	information-and-network-security	robots llmsaihumans	emailphone	none
cavexia.ai ↗	68 match 2 shared topics	Cavexia — Security for the agentic stack	US~ en	information-and-network-security	robots llms ai humans	emailphone	none
cavexia.com ↗	68 match 2 shared topics	Cavexia — Security for the agentic stack	US~ en	information-and-network-security	robots llmsaihumans	emailphone	none
use-saltsecurity.com ↗	68 match 2 shared topics	Salt Security: Agentic AI Security, MCP Discovery, and API Security	US~ en	information-and-network-security	robotsllmsaihumans	emailphone	none
salt-securityteam.com ↗	68 match 2 shared topics	Salt Security: Agentic AI Security, MCP Discovery, and API Security	en	information-and-network-security	robotsllmsaihumans	emailphone	none
salt-securityhq.com ↗	68 match 2 shared topics	Salt Security: Agentic AI Security, MCP Discovery, and API Security	en	information-and-network-security	robotsllmsaihumans	emailphone	none
salt-securitydirect.com ↗	68 match 2 shared topics	Salt Security: Agentic AI Security, MCP Discovery, and API Security	en	information-and-network-security	robotsllmsaihumans	emailphone	none
saltsecurity.io ↗	68 match 2 shared topics	Salt Security: Agentic AI Security, MCP Discovery, and API Security	en	information-and-network-security	robotsllmsaihumans	emailphone	none
userecoaiteam.com ↗	68 match 2 shared topics	AI Agent Security Platform \| Reco	en	information-and-network-security	robotsllmsaihumans	emailphone	none
joinrecoaiteam.com ↗	68 match 2 shared topics	AI Agent Security Platform \| Reco	en	information-and-network-security	robotsllmsaihumans	emailphone	none
defendai.tech ↗	68 match 2 shared topics	DefendAI — The control plane for agentic AI security	en	information-and-network-security	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.