The difference between AI text and publish-ready content.
Generic AI writers hand you a wall of text. We hand you a structured, SEO-tuned, schema-tagged article that's been through eight editorial passes and a live fact check — ready to drop straight into your CMS in any of 40+ languages.
What makes this different
Built-in SEO discipline, not an afterthought
Most AI writers happily produce text that violates basic on-page SEO: missing H1, scattered keyword stuffing, no meta description, no schema. Our pipeline enforces them programmatically — one H1, clean H2/H3 hierarchy, keyword density between 0.5%–1.5%, meta title under 60 characters, description under 155, kebab-case slug. Every article. Every time.
Eight editorial passes, not one generate-and-done
We don't ask Claude to 'write an article' in one shot. We run keyword strategy, infer the competitive landscape, build the outline, draft against it, do a dedicated SEO pass, humanize the prose (sentence variety, AI-tell removal, contractions), then finalize with schema. Each step is its own model call with its own prompt — the equivalent of a junior writer, an editor, and an SEO specialist working in sequence.
Featured-snippet ready, on purpose
The first H2 of every article is structured as a direct-answer block — concise, scannable, the format Google promotes to position zero. Most AI writers bury the answer under five paragraphs of context. We put it where the algorithm looks for it.
40+ languages with native regional voice
Not machine translation. The article is written from scratch in the target language — Spanish (Spain vs Mexico vs LatAm), Portuguese (Brazil vs Portugal), Chinese (Simplified vs Traditional), and 30+ more. Regional spelling, idioms, and examples adjust automatically. JSON-LD inLanguage tag set correctly for every output.
Schema markup, generated automatically
Every article ships with a complete schema.org Article JSON-LD block — headline, description, inLanguage, datePublished, keywords, articleBody summary. Validates clean against Google's Rich Results test. Most AI tools don't touch schema; the few that do require manual configuration.
Revisions are a workflow, not a re-order
Don't like a section? Type 'tighten the intro and add a part about pricing' — we run a targeted 2-step revision pass that preserves the rest of the article and applies your changes. Costs half the original credits, minimum 100. Old version is archived so you can compare.
Pay-per-word. Credits never expire.
No subscription. No 'use it or lose it' monthly quota. Buy 1,000 credits or 50,000 credits — the per-word rate is flat 4¢ across every pack. Pipeline failure for any reason refunds your credits automatically, the same day.
The 9-step pipeline, explained
You watch each step finish live on the order page. Every step's output feeds the next — and every step has its own focused prompt, optimized for that single job.
- 01Research and keyword strategyWeb search against live sources so the plan reflects what is true now, not what a training set remembers. Search intent classification, 15–20 semantic variants, 8–10 FAQ-style question variants, and an estimated depth benchmark for the topic.
- 02Competitive contextInferred patterns from how top results typically frame this query, plus content gaps a new article can claim.
- 03OutlineH1, 5–8 H2s with H3 subsections where needed. First H2 reserved for the direct-answer snippet candidate. FAQ H2 with question-style H3s near the end.
- 04DraftFull-length article written against the approved outline, with related keywords woven in naturally and contractions used where appropriate to the target language.
- 05SEO passKeyword placement verified, density measured and corrected if needed, heading hierarchy validated, meta title + description + slug + internal-link anchors generated.
- 06Editorial polishSentence-length variation enforced. AI-tell phrases removed in the target language. Tricolons cut. Em-dashes capped at two per article. Reading level tuned to roughly grade 8.
- 07Fact checkEvery checkable claim — statistics, dates, prices, named products, regulatory assertions — is verified against live web results. Contradicted claims are corrected as targeted swaps, so the article keeps the voice and the length you paid for. Unverifiable claims are flagged rather than invented around.
- 08FinalizeMarkdown converted to clean semantic HTML. JSON-LD Article schema generated with inLanguage. Four download formats ready: Markdown, Markdown + frontmatter (Hugo / Astro / Jekyll), HTML, JSON-LD.
- 09Strip AI watermarksEvery invisible character models leave behind is removed: zero-width spaces, joiners and non-joiners, word joiners, byte-order marks, bidi controls, variation selectors, and the Unicode tag block that can hide whole messages inside ordinary-looking text. Non-standard spaces are folded to regular ones. Nothing shows up in your CMS or your diffs.
Versus the alternatives
- ✗Manual prompt engineering every time
- ✗No SEO discipline by default
- ✗No schema, no slug, no meta
- ✗Output quality depends on your prompt skill
- ✗One single pass — no editing loop
- ✗Often write SEO-violating prose
- ✗Limited language support
- ✗Schema markup is rare or manual
- ✗Subscription pricing (use it or lose it)
- ✗No structured revision workflow
- ✗$50–$500 per article, 3–10 day turnaround
- ✗Inconsistent voice across writers
- ✗SEO knowledge varies wildly
- ✗Schema markup almost never included
- ✗Language coverage limited to writer pool
Try it on one article.
1,000 credits gets you a full-length article through the entire pipeline. If you don't like it, request a revision — or use the refund-on-failure path that's built in.