Landing pages
AI search landing pages
Pages that explain a product, category, or service in language answer engines can parse and quote.
Module 02 · Workspace ContentOS
The content agent for AI Search visibility. Measure the gap, produce the proof, approve the page.
ContentOS turns a visibility gap into a governed content packet: brief, draft, schema, quality report, and proof receipts.
Hermes and AI Visibility show where your brand is missing. Parsing Stack gathers the source evidence. Workspace ContentOS writes the page or article, runs quality gates, stores every artifact in Workspace Files, and keeps publishing draft-only until a human approves.
Gap
Packet
Proof
RUN packet
- Brief
- Draft
- Schema
- Gates
Optimized for
- ChatGPT
- Claude
- Perplexity
- Gemini
- Grok
- DeepSeek
- Kimi
- Google AIO
- Copilot
AI content operations, not prompt output
AI search does not reward generic volume. It rewards content that can be trusted, parsed, and cited.
The market has moved from "write me a blog post" to "close this citation gap." Buyers ask ChatGPT, Perplexity, Gemini, Claude, Copilot, Google AI Overviews, Yandex Neuro, Alice, and DeepSeek which company to choose.
Those systems do not just need a page; they need clear answers, source-backed claims, structured sections, schema, and enough trust signals to cite. Workspace ContentOS is the production side of that loop.
It is a repeatable operating packet.
Instead of handing the gap to a freelance writer and hoping the page is useful, ContentOS builds a packet with evidence, gates, artifacts, and receipts.
01 · Measure and source
Find the gap and gather evidence
Hermes and AI Visibility identify the engines, prompts, competitors, and missing source types. Parsing Stack fetches SERP results, source pages, structured facts, and citation candidates.
02 · Produce and gate
Generate the brief, draft, and repairs
ContentOS creates the page brief, drafts the asset, then scores publish-readiness, citation integrity, factcheck, readability, uniqueness, AI-likeness, and AEO/GEO readiness.
03 · Store and approve
Save the packet before anything ships
Workspace Files receives the brief, draft, schema, gate results, quality report, and JSON receipt. Publishing stays draft-only until a human or scoped publishing agent approves.
Output packet
Brief, draft, schema, report
Every run can produce brief markdown, final article or page markdown, schema JSON-LD, quality report markdown, final uplift JSON, gate results JSON, and a contentos-package receipt. The operator sees more than "here is the text."
Quality gates
Uniqueness, AI-likeness, citations
Commercial pages are checked for high uniqueness, low AI-likeness, factual support, source fidelity, grammar, readability, and AEO/GEO readiness. Russian pages add native editorial and claim-fidelity gates.
Governance
Workspace key, scope, approval
The agent runs through scoped Workspace API keys, records artifacts, and keeps publishing draft-only. That gives teams velocity without losing control over brand claims, legal risk, and client approval.
Open-source Lite version
Try the ContentOS process in your own repo. Upgrade when you need the managed workspace loop.
ContentOS Agent Lite is the MIT-licensed open-source skeleton of the agent: seven gates from business context and source pack to draft quality, editorial uplift, and publish readiness.
It runs locally in Claude Code, Cursor, or Codex with zero required API keys, and optional Python helpers can make research and scoring more repeatable. Use Lite to inspect the operating method, adapt it to a founder workflow, or teach a coding agent how to produce grounded content.
Lite
Free local skeleton
Process files, transparent gates, local scoring, EN/RU/AR checks, and bring-your-own optional research keys.
Workspace
Managed team pipeline
AI Visibility inputs, Parsing Stack evidence, Workspace Files artifacts, source QA, repair loops, team keys, approvals, and publish handoff.
What teams use it for
ContentOS is strongest where AI engines need a clean answer and a trusted source path.
Comparisons
Comparison and best-of assets
Structured buyer pages that answer comparison prompts and give models clean sections to cite.
Explainers
Citation-ready explainers
Research-backed articles with source constraints, entity anchors, FAQ sections, and schema.
Refresh
Stale page upgrades
Existing pages rewritten around current visibility gaps instead of old SEO assumptions.
RU
Native Russian content
RU pages for Yandex Neuro, Alice, and Russian-language buyer questions with native editorial gates.
FAQ
Questions teams ask before they let an agent write.
What does Workspace ContentOS produce?
A ContentOS run produces a RUN packet for the workspace: brief markdown, final article or page markdown, quality report, schema JSON-LD, final uplift JSON, gate results JSON, and a contentos-package JSON receipt. Workspace Files stores the artifacts so the operator can inspect, approve, reuse, or hand them to publishing.
How is this different from an AI writing tool?
An AI writer returns prose. Workspace ContentOS runs a governed content operation: visibility gap, source evidence, brief, draft, quality gates, repair loop, artifacts, and approval. It is built for citation-ready AEO/GEO pages, not one-prompt blog output.
Which quality gates matter before approval?
The current Workspace gates include publish-readiness, final uplift, citation integrity, grammar, readability, factcheck, uniqueness, AI-likeness, AEO/GEO readiness, and language-specific editorial gates for native Russian work. Commercial and service pages target high uniqueness and a low AI-likeness score before the packet is considered ready.
Does ContentOS publish automatically?
No. The production policy is draft-only. ContentOS prepares the page, proof packet, schema, and handoff; a human or a scoped publishing agent approves the next step. That keeps client claims, legal risk, and brand voice under operator control.
Where does the research come from?
Hermes Visibility and AI Visibility show which questions and competitors matter. Parsing Stack fetches pages, SERP evidence, and structured source material. ContentOS uses that evidence to create the brief and draft instead of inventing facts from model memory.
Can it handle Russian pages?
Yes. The Workspace ContentOS contract includes native Russian gates for editorial quality, source fidelity, claim fidelity, style profile, transcreation, and SEO naturalness. Russian output is treated as native content, not a machine-translation pass.
What happens when a gate fails?
The run does not pretend the draft is ready. ContentOS records the failed gate, runs a bounded repair loop when allowed, and leaves a readable proof trail. The operator can see whether the issue is uniqueness, AI-likeness, citations, factual support, structure, or source quality.
See which content gaps AI engines already notice. Then turn one into a packet.
We run your brand through Hermes, choose one high-leverage gap, and show how ContentOS would turn it into approved work.
You see the actual operating loop: measurement, source evidence, draft, gates, proof receipts, and the approval step before anything goes live.