InLinks Review: Entity-Based Internal Linking That AI Platforms Actually Follow

The Short Answer

InLinks takes a fundamentally different approach to internal linking by building connections around entities rather than keywords. At £25/mo, it is one of the more affordable tools that directly addresses how AI platforms parse and understand website content. It is not perfect — the UI needs work and integrations are limited — but for content-heavy B2B sites, the entity-first methodology solves a real structural problem that most SEO tools ignore.

The Problem InLinks Solves

Most internal linking tools work on keyword matching. Page A mentions "marketing automation," page B targets "marketing automation," so they suggest a link between them. This works for traditional SEO. It does not work for AI visibility.

AI platforms do not read websites the way Google's crawler does. They parse entities — people, companies, concepts, products — and map relationships between them. When ChatGPT or Perplexity decides whether to cite your site, they are evaluating whether your content demonstrates clear topical authority through connected entity relationships. A site with 200 blog posts linked by keyword overlap looks different to an AI model than a site with 200 blog posts linked by entity relationships.

InLinks addresses this gap directly. Instead of matching keywords across pages, it builds an entity graph of your content and creates internal links based on how those entities relate to each other.

How It Works

InLinks operates in four layers:

Entity analysis. You connect your site and InLinks crawls it, identifying every entity mentioned across your content. It maps these against knowledge bases to understand what each entity is and how entities relate to each other. This produces a visual entity graph showing your site's topical coverage.

Automated internal linking. Based on the entity graph, InLinks generates internal links via a JavaScript snippet. These links connect pages through entity relationships, not keyword matching. The system adds links dynamically without requiring you to edit individual posts.

Schema markup generation. InLinks generates entity-based schema markup (JSON-LD) for your pages. This is the structured data that helps search engines and AI crawlers understand what a page is about at a machine-readable level. The schema ties into the entity graph, so the markup reflects actual topical relationships rather than generic page-level schema.

Content briefs. The platform generates content briefs that identify entity gaps in your coverage. If your entity graph shows strong coverage of "marketing automation" but weak connections to related entities like "lead scoring" or "workflow orchestration," InLinks flags this as a content opportunity.

How We Tested It

We evaluated InLinks against the three AI visibility dimensions it claims to address: entity recognition, content structure, and technical markup. Specifically, we looked at whether its entity analysis matched what AI platforms actually recognise when queried about a brand, whether its internal linking structure improved content discoverability for AI crawlers, and whether its schema output met current structured data standards.

We also compared the entity graph InLinks produces against manual entity mapping we had already done through our AI Visibility Benchmark scanning process, where we assess how AI platforms describe and categorise companies.

What It Does Well

Entity gap analysis is genuinely useful. Most content audit tools tell you which keywords you are missing. InLinks tells you which entity relationships are weak or absent. This is a more useful signal for AI visibility because AI platforms evaluate topical authority through entity connections, not keyword density.

The pricing is fair. At £25/mo for the base plan, InLinks costs less than a single month of most enterprise SEO tools. For a B2B site with 50-200 pages of content, the entity analysis alone provides enough value to justify the cost.

Automated linking removes a real bottleneck. Manual internal linking across a growing content library is tedious and inconsistent. The JavaScript-based automation means links update as new content is published, without requiring someone to retroactively edit older posts.

Schema generation covers a gap. Many B2B sites have no schema markup at all, or only basic page-level schema. InLinks generates entity-aware markup that goes beyond what most WordPress plugins produce.

Where It Falls Short

InLinks is a smaller company. Support resources are thinner than what you get from Semrush or Ahrefs. Documentation exists but is not comprehensive. If you hit an edge case, expect to wait longer for answers.

The UI is functional, not refined. The dashboard works, but it feels like a tool built by engineers for engineers. Navigation is not always intuitive, and some reports require extra clicks to reach useful data. This is not a dealbreaker, but teams used to polished SaaS interfaces will notice.

Integrations are limited. InLinks works primarily through its own dashboard and a JavaScript snippet. There is no native integration with most CMS platforms beyond WordPress, and API access for custom workflows is constrained. If your tech stack requires deep integrations, factor in manual workarounds.

How It Maps to AI Visibility

InLinks touches three of the four AI visibility dimensions we measure in our benchmark work:

Dimension	InLinks Coverage	Assessment
Entity Recognition	Direct	Entity analysis and schema markup directly improve how AI platforms identify and describe your company
Content Structure	Strong	Entity-based internal linking creates the topical clusters AI crawlers use to evaluate authority
Technical (Schema)	Direct	JSON-LD generation provides machine-readable entity data
Citation Presence	Indirect	Better entity structure contributes to citation probability, but InLinks does not measure or track citations directly

The tool does not address citation breadth (off-site mentions), which is expected. No on-site tool can control third-party mentions.

Who Should Use It

InLinks fits a specific profile: B2B companies with content-heavy websites (50+ pages) that need better internal linking structure and have weak or absent schema markup. If your site has hundreds of blog posts linked loosely or not at all, InLinks will create more value than manually auditing every post.

It is less useful for small sites with under 20 pages, companies that already have strong entity-based schema through custom development, or teams that need deep CMS integrations beyond WordPress.

Pricing

InLinks operates on a credit-based system starting at £25/mo. Credits are consumed by page analysis, link generation, and content briefs. For a site with 100-200 pages, the base plan is typically sufficient. Larger sites or agencies managing multiple domains will need higher tiers. There is no free tier, but the entry cost is low enough to evaluate over a single month without significant commitment.

Rating: 4/5 — A focused tool that does one thing well. The entity-based approach is structurally sound for AI visibility. Loses a point for UI polish and integration limitations.