Google Ranks Pages.
AI Cites Meaning.
Stop optimizing keywords. Start architecting retrievability. Measure the semantic density, entity gaps, and structural fixes AI needs to cite your content.
60-second analysis · 7-day free trial
Your Content Is Either the Source or the Footnote.
58.5% of searches now end without a click. AI Overviews grew 102% in the last year. When AI systems summarize your market, they choose which content to cite based on semantic architecture, not keyword rankings. Content without explicit entity definitions, structured relationships, and meaning coherence doesn't get ignored. It gets replaced by content that has them.
Other Tools Give You Scores. You Need Architecture.
| What other tools tell you | What you actually need |
|---|---|
| “Your content score is 67/100” | “Entity ‘usage-based pricing’ appears 6 times but is never defined” |
| “Entity coverage needs improvement” | “Add this 2-sentence definition in paragraph 3” |
| “Consider adding more semantic depth” | “Connect ‘pricing strategy’ to ‘customer value’ with this bridging sentence” |
How It Works
Three steps to actionable semantic fixes
Submit Your Content
Enter any public URL or paste draft text before publishing.
Semantic Architecture Extraction
In 60 seconds, we map every entity, relationship, and structural gap AI systems evaluate when deciding whether to cite your content.
Prioritized Fix Architecture
Specific recommendations with example rewrites, ranked by retrieval impact. Not just what's wrong, what to write and where to put it.
Different Category. Not Just Different Features.
| Capability | Keyword Tools (Clearscope, Surfer) | AI Writing Tools (Jasper, Copy.ai) | DecodeIQ |
|---|---|---|---|
| Entity extraction & analysis | ○ | ○ | ● |
| Specific fix recommendations | ○ | ○ | ● |
| AI retrieval prediction | ○ | ○ | ● |
| Relationship mapping | ○ | ○ | ● |
| Keyword optimization | ● | ○ | ○ |
| Content generation | ○ | ● | ○ |
DecodeIQ isn't a better SEO tool. It's a different layer entirely. SEO tools optimize for Google's ranking algorithm. DecodeIQ engineers the semantic architecture that AI systems evaluate when choosing what to cite.
What's Inside Every Analysis
Entity Gap Analysis
See exactly which concepts are defined, which are mentioned but undefined, and which critical entities are completely missing from your content.
Prioritized Fix List
Not just problems, solutions. Each fix includes priority level, estimated effort, and example text you can adapt.
Retrieval Prediction
Know which queries your content is likely to be retrieved for, uncertain on, or will probably miss entirely.
Relationship Mapping
Visualize how your concepts connect. Strong relationships help AI understand context; weak or missing ones create blind spots.
This is what AI “sees” when it evaluates your content. Weak and missing connections are why content gets skipped.
Two Ways to Use It
Will AI systems actually retrieve this draft?
- ✓Check drafts before they go live
- ✓Catch missing definitions early
- ✓Build retrieval-ready content from the start
Why isn't my content showing up in AI?
- ✓Analyze published pages that should rank but don't
- ✓Find semantic gaps competitors have filled
- ✓Get specific fixes without rewriting from scratch
Built for Tech, Not Everything
Our semantic models are trained specifically on technology content patterns.
Works Great For
- ✓ SaaS product documentation
- ✓ Developer tool guides
- ✓ Cloud infrastructure content
- ✓ API and integration articles
- ✓ Technical comparison pieces
Not Calibrated For
- ✕ Healthcare / Medical content
- ✕ Legal or financial advice
- ✕ News or journalism
- ✕ E-commerce product descriptions
- ✕ Entertainment or lifestyle
Sample Report Preview
What you'll get when you analyze a page
This is what “architecting retrievability” looks like in practice.
This term appears 6 times but is never explained.
“Usage-based pricing is a billing model where customers pay based on their actual consumption of a product or service, rather than a flat subscription fee.”
Get your full report with all fixes and example rewrites
Get Your Full ReportThree Metrics That Predict AI Retrievability
Every report includes these research-validated measurements
Semantic Density
Entity concentration per 1,000 words. Measures relationship depth and concept specificity. Low density means content lacks sufficient entity structure for AI retrieval.
Contextual Coherence
Logical flow consistency score. Evaluates how well concepts chain together across segments. Low coherence means scattered topical focus that retrieval systems struggle to categorize.
Retrieval Confidence
Likelihood of being surfaced in AI-driven search results. Based on semantic proximity to high-performing technology content corpus (n=1,200+ articles).
These aren't arbitrary scores. Each metric is calibrated against 1,200+ technology articles with documented retrieval outcomes.
Start Engineering. Scale When Ready.
7-day free trial on all plans. Cancel anytime.
Every plan includes the full semantic analysis engine. Choose based on volume, not feature gates.
Basic
- ✓10 pages/month
- ✓Basic report (scores + entity analysis)
- ✓Top 3 fixes only
- ✓48-hour report history
Starter
- ✓30 pages/month
- ✓Full report + example fixes
- ✓All fixes with example rewrite text
- ✓30-day report history
Pro
- ✓100 pages/month
- ✓Full report + example fixes
- ✓Unlimited report history
- ✓Export (PDF/CSV)
- ✓Coming soon
All plans include a 7-day free trial. Credit card required. Cancel before trial ends and you won't be charged.
Frequently Asked Questions
What does “semantic analysis” mean?▼
What types of content can I analyze?▼
How is this different from Clearscope or Surfer?▼
How accurate are the retrieval predictions?▼
Can I analyze competitor pages?▼
What happens to my content after analysis?▼
Do I need to change my workflow?▼
Stop Optimizing Keywords. Start Architecting Meaning.
Measure your content's retrieval confidence in 60 seconds.
Measure Retrieval Confidence