AI Content Editor:
Research-First Writing, Not Prompt-and-Pray
Most AI writing tools generate first and hope the model's training data was current. This one runs Perplexity and live SERP research before it writes a word, keys every section to a real People Also Ask question, and QA-scores the draft for citation readiness before you publish.
Generated First, Researched Never - Until Now
Ask a typical AI writing tool to cover a topic and it draws on the model's training data alone - no live sense of what's currently ranking, what questions people are actually asking right now, or which sources the top pages cite. The result reads fine and is quietly disconnected from the actual search landscape.
This editor runs Perplexity and DataForSEO SERP research in parallel first, pulling real People Also Ask questions, cited sources, and a live outline of what's ranking, before generating anything. Every section that gets written is answering a question people are actually asking, not a heading the model invented.
Four Phases, Research to Export
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Research
Perplexity and DataForSEO SERP research run in parallel, surfacing People Also Ask questions, cited sources, and a live outline of what's currently ranking.
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Generate, Section by Section
Each section of the outline is keyed to a real PAA question from the research, not an invented heading, and generated with that research context in place.
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QA for Citation Readiness
The draft is scored against real PAA coverage, citation readiness, and attribution gaps using Gemini, with the original research context included in the check.
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Export With Schema
PAA-keyed Q&A sections export with FAQPage JSON-LD already generated from the same source material.
Frequently Asked Questions
- What makes this a "research-first" content editor?
- Before generating a single section, it runs Perplexity and DataForSEO SERP research on your target query in parallel, pulling People Also Ask questions, cited sources, and an outline of what's already ranking. The content it generates is built from that research, not from the model's own unsourced assumptions about the topic.
- What does "PAA-keyed sections" mean?
- Each section of the generated outline is tied to a real People Also Ask question pulled from live search data, rather than a heading the model invented. That keeps the structure aligned with what people are actually asking, and makes each section a natural candidate for FAQ schema.
- What does the QA scoring check?
- It scores the draft against real PAA coverage (how many of the researched questions the content actually answers), citation readiness (whether answers sit in clean, quotable passages), and attribution gaps (claims made without a traceable source), using Gemini with the original research context included.
- Can I export with schema markup already included?
- Yes - the PAA-keyed Q&A sections export with FAQPage JSON-LD already generated, so the schema and the content it describes are built from the same source material rather than added separately afterward.