content velocity without the content team

mode: programmatic seo // quality_gates: 12 // optimization: llm_grounding // output: direct to cms

Built for b2b companies that need 400 pages, not 12 blog posts. Running in production.

01 // the problem

your category leader published 400 pages last year. you published 12.

That gap compounds for 18 months. It's not blog volume — it's topical authority and GEO coverage. Perplexity, ChatGPT Search, and Gemini index companies with dense content graphs.

A content writer produces 1-2 articles per week at $80-150K/year. Monad Pages generates validated, structured content on schedule — with 12 automated quality gates that enforce standards no human team maintains consistently.

# monad pages — production pipeline
engine: "pagezilla_v2"
validators: 12

# stage 1: research
gsc_ingest()semantic_silence_map()
gaps: competitor coverage vs. your index
source: google search console + serp analysis

# stage 2: generation
content_factory()pydantic_validate()
word_count: ≥1800 enforced
diagrams: ≥2 d2/kroki per article
banned_words: 47 terms filtered

# stage 3: publish
hitl_review()modx_bridge.post()
indexnow: immediate submission
optimization: llm_grounding

status: pipeline operational
02 // the pipeline

four stages. zero manual steps between them.

stage 01

research

Google Search Console ingestion + semantic silence mapping. Finds the gaps in your market's search landscape that competitors haven't covered — and ranks them by opportunity.

stage 02

generation

LLM routing across specialized models: reasoning model for structure, writing model for prose, validation model for quality. Each article gets D2 diagrams rendered via Kroki API.

stage 03

validation

12 automated gates: word count ≥1800, ≥2 diagrams, banned word filter (47 terms), TL;DR section, FAQ schema, internal linking, meta fields, GEO optimization. Nothing ships without passing all 12.

stage 04

publish

Human-in-the-loop review, then direct publish to your CMS via API bridge. IndexNow submission for immediate indexing. AI overview optimization for citation by Perplexity, ChatGPT, Gemini.

03 // proof

measured in production.

12
quality gates
per article
≥1800
words enforced
minimum
≥2
diagrams
per article
47
banned words
filtered
>95%
cost reduction
vs. writers
GEO
optimized for
ai overviews
API
direct cms
publish
24/7
autonomous
pipeline
04 // what makes this different

three things this is not.

not templates

Every article is generated from research data, not filled into a template. Structure adapts to the topic. No two articles share the same outline.

not ai slop

12 validators catch the problems that make AI content obvious: repetitive phrasing, banned buzzwords, missing structure, shallow analysis. If it doesn't pass, it doesn't ship.

not one-shot

The pipeline runs on schedule. New topics surfaced from GSC data, generated, validated, reviewed, published. Continuous content velocity, not a one-time batch.

05 // deployment

see monad pages on your content pipeline.

15-minute architecture review. We'll map your current content approach against what Pages would replace — with specific volume and quality projections for your market.

[ audit pipeline ]
built for b2b content — saas documentation, professional services insights, technical blogs. not for e-commerce product descriptions or social media.