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Venelu | How AI is Transforming the Future of CRM Systems — 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
vtiger.com ↗	60 match shared topic	Best CRM Software – All in One AI-Powered CRM Platform \| Vtiger	en	artificial-intelligence Prismic	robotsllmsaihumans	emailphone	none
outsystemsenterprise.com ↗	60 match shared topic	Your AI development platform built for the enterprise \| OutSystems	United States~ en	artificial-intelligence	robotsllmsaihumans	emailphone	none
fireflies.ai ↗	60 match shared topic	Fireflies.ai \| #1 AI Assistant for Meetings, Email, Chat & CRM	en	software-and-applications	robotsllmsaihumans	emailphone	none
outsystems.com ↗	60 match shared topic	Your AI development platform built for the enterprise \| OutSystems	United States~ en	artificial-intelligence	robotsllmsaihumans	emailphone	none
creatio.com ↗	60 match shared topic	AI CRM and Workflow Platform \| Creatio	en	artificial-intelligence Drupal	robotsllmsaihumans	emailphone	none
klono.ai ↗	60 match shared topic	Future Commerce Platform	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
agenticdeveloperecosystems.com ↗	60 match shared topic	Agentic Developer Ecosystems	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
agno.com ↗	60 match shared topic	Agno: Agent Framework and High-Performance Runtime for Multi-Agent Systems	en	software-and-applications	robots llmsaihumans	emailphone	none
speechelo.com ↗	60 match shared topic	Text To Speech Software, Transforming Text to Voice Instantly - Speechelo	en	artificial-intelligence WordPress WooCommerce	robotsllmsaihumans	emailphone	none
artilisa.com ↗	60 match shared topic	Artilisa \| Homepage \| The future is now	en	software-and-applications	robotsllmsaihumans	emailphone	none
wippy.ai ↗	60 match shared topic	The runtime for agentic systems \| Wippy	en	software-and-applications	robots llmsaihumans	emailphone	partial · 14
betasystems.com ↗	60 match shared topic	Powering Autonomous IT Operations with Intelligent Automation & Orchestration – Beta Systems	Germany~ en	artificial-intelligence Storyblok	robotsllmsaihumans	emailphone	none
lovable.dev ↗	55 match shared topic	AI App Builder \| Vibe Code Apps & Websites with AI, Fast	en	artificial-intelligence	robots llmsaihumans	emailphone	none
livechat.com ↗	55 match shared topic	LiveChat® - The Best AI Live Chat Software for Business \| LiveChat.com	United States~ en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
livechatinc.com ↗	55 match shared topic	LiveChat® - The Best AI Live Chat Software for Business \| LiveChat.com	United States~ en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
gitlab.com ↗	55 match shared topic	Finally, AI for the entire software lifecycle.	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
livechatenterprise.com ↗	55 match shared topic	LiveChat® - The Best AI Live Chat Software for Business \| LiveChat.com	United States~ en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
airtable.com ↗	55 match shared topic	Airtable: Build Enterprise-ready AI Workflows, Apps & Agents \| Airtable	en	software-and-applications Sanity	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.