Automated keyword research and clustering
Automatically finds relevant keywords, groups them by search intent, and builds keyword clusters without manual spreadsheet work.
Machined
Freemium
Automatisation du contenu SEO : mots-clés, clusters, liens et publication
Qu'est-ce que Machined ?
Machined is a content cluster automation platform for SEO teams and publishers that want to build topical authority with less manual coordination. It combines keyword research, clustering, content generation, internal linking, research-backed citations, and publishing in one workflow.
The product is built around a cluster-based SEO process: enter a topic or seed keyword, let the system discover and organize related keywords, generate a pillar page and supporting articles, connect them with internal links, and send the finished cluster to a CMS. The pricing page also shows free and paid plans, with publishing integrations for WordPress, Webflow, and webhooks.
Que peut faire Machined ?
Content cluster automation
Creates pillar pages and supporting articles as a content cluster, with built-in anti-cannibalization logic so articles target distinct long-tail keywords.
Automatic internal linking
Reads articles in a cluster, identifies contextual linking opportunities, and inserts internal links with optimized anchor text.
Deep AI research with citations
Uses agent-based research and authoritative citations so articles are based on sourced material rather than unsupported generation.
One-click publishing
Publishes content to WordPress, Webflow, or webhook-based workflows, including drafts or direct publishing depending on the setup.
Customization and editorial control
Lets teams control voice, research depth, and AI models, with additional support for custom briefs, editing, and meta title/description generation.
Cas d'utilisation
“Build topical authority around a core topic”
Teams planning pillar pages and supporting articles can use Machined to turn a seed topic into a structured cluster with distinct search intents.
“Reduce keyword cannibalization”
SEO teams can automate keyword grouping and article targeting to reduce the chance that multiple pages compete for the same query.
“Scale internal linking across many articles”
Publishers and agencies can use the internal-linking workflow to add contextual links across a cluster without manual anchor-text editing.
“Send content into a CMS workflow”
Teams that publish to WordPress or Webflow can generate a cluster and push drafts or finished articles into their CMS instead of copying content manually.
“Produce researched content at scale”
Companies that need research-backed articles can use the citation and deep-research workflow to support long-form content with sourced references.
Questions fréquentes
What is Machined for?
Machined is designed to automate SEO content cluster workflows, including keyword research, clustering, content generation, internal linking, and publishing. The site positions it for people building topical authority at scale.
Can Machined publish directly to a CMS?
The site describes support for WordPress, Webflow, and webhook integrations for publishing and CMS connections.
How does Machined avoid keyword cannibalization?
Machined says it can automatically research and cluster keywords by search intent, which helps separate topics into distinct articles and reduce overlap between pages.
Is there a free trial or free plan?
The pricing page shows a free plan, a 3-day free trial on the Launch plan, and paid plans that scale by article volume and team size.
How many languages does Machined support?
The site says Machined supports more than 100 languages.
Informations rapides
- Category
- SEO content automation
- Platform
- Web app
- Primary workflow
- Keyword research, clustering, content generation, internal linking, publishing
- Integrations
- WordPress, Webflow, webhooks
- Languages
- 100+ supported
- Pricing
- Free plan and paid plans; 3-day free trial on Launch
Analyse du trafic de Machined
Les données de trafic sont fournies à titre indicatif uniquement.
- Évaluation du domaine
- 56
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