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integrated.finance

integrated.finance

Moderate AI visibility with 28 of 48 criteria passing. Biggest gap: llms.txt file.

54/100
D
Citation Avg
Coherence gate active - score capped at 60
Answer Readiness
~40% weight
7/10
Content Structure
~25% weight
6/10
Trust & Authority
~15% weight
4/10
Technical Foundation
~10% weight
5/10
AI Discovery
~10% weight
5/10

Verdict

Below-average AEO readiness at 54/100 - multiple areas need attention. Key strengths include Sitemap Completeness, Direct Answer Paragraphs, and Content Cannibalization. Priority gaps: llms.txt File, Schema.org Structured Data, and RSS/Atom Feed. Topic coherence is moderate at 5/10, capping the score at 60. Tighter topical focus would lift this ceiling.

#2965of 13363
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How to Improve

Current
54/100
Projected
82/100
41Total Fixes
12Quick Wins
~75hEst. Effort
Quick Wins
Create /llms.txt fileStrengthen entity authority (NAP)Configure robots.txt for AI crawlersAdd content freshness signalsAdd structured tables and listsAdd definition-style contentAdd ai.txt and content licensingEnhance author and expert schemaFix canonical URL strategyFocus blog content on core expertiseClarify entity boundariesReduce document weight
Create /llms.txt file
critical|low
Add llms-full.txt with extended content
medium|low
Reduce document weight
high|low
Configure robots.txt for AI crawlers
high|trivial
Fix canonical URL strategy
critical|low
Add internationalization signals
critical|medium
Fix HTML structure and meta tags
low|low
Improve server response efficiency
low|low
Reduce render-blocking resources
low|low

Top Opportunities10

Ensure blog content consistently covers your core expertise areas rather than scattering across unrelated topics. AI engines build authority models - a site about "Medicare coverage" that also publishes about humidifiers and groceries dilutes its topical authority.

Include "our analysis", "our data", "our testing" phrases backed by original research or proprietary data. 52.2% of AI-cited posts contain owned data signals.

Use HTML tables for comparison data and ordered/unordered lists for features, steps, and specifications. Structured data formats are directly extractable by AI engines for answers.

Ensure every question-format heading (H2/H3) is followed by a direct answer paragraph. This pattern is ideal for AI engine snippet extraction.

Place a concise 40-80 word answer block in the first 300 words of each page. Avoid throat-clearing openers like "In this article..." and lead with the answer.

Define the primary entity in the first 500 characters, use consistent terminology (same term 70%+), and add "unlike X" signals to help AI engines distinguish your topics.

Implement JSON-LD structured data (Organization, Service, Product, FAQPage) on key pages. Schema markup helps AI engines extract and cite your content accurately.

Show direct use, testing, implementation, or lived experience with concrete observations, examples, screenshots, and lessons learned.

Add question-based headings (H2/H3) throughout your content. Use "What is...", "How does...", "Why should..." patterns that match how users query AI assistants.

Create a dedicated FAQ page with FAQPage schema markup. Cover common questions about your products, services, and industry to become a direct answer source for AI engines.

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Site Pages

integrated.finance/building-blocks/open-banking-providers...F32
Building blocks | Open Banking Providers
integrated.finance/insights/blogs/comprehensive-overview-...D44
A comprehensive overview of SWIFT
integrated.finance/case-studies/silverbirdD41
Silverbird launches in niche trade markets
integrated.finance/ways-to-use-if/infrastructureF37
Infrastructure
integrated.finance/infrastructure-for/platformsD40
Embedded Banking for Platforms

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