Free
- Concurrent pipelines
- 1
- Parallel inputs
- 1
- Results per month
- 10
- Tests per day
- 3
AI CONTENT PIPELINE FOR WEB PUBLISHING
AI content pipeline for SEO and WordPress
Sources, RAG, AI steps, review and publishing in one visible workflow.
Publishing workflow
- keyword
- sources
- RAG
- AI steps
- review
- publish
Execution
- intent
- queries
- search
- fetch
- context
- writer
- editor
- article form
A working pipeline from the first run
The free plan includes one slot and one thread. A template, provider connection and WordPress or CMS endpoint are enough for a complete test run.
plans
| Features | Free Free | Top · best choice Starter 10 USDT / period | Pro 29 USDT / period | Agency 79 USDT / period |
|---|---|---|---|---|
| Concurrent pipelinesPipelines that can run at once | 1 | 2 | 5 | 10 |
| Parallel inputs per pipelineInputs processed in parallel | 1 | 2 | 4 | 8 |
| Successful results per monthFinal production results | 10/month | Unlimited | Unlimited | Unlimited |
| Template tests per dayTesting before production | 3/day | Unlimited | Unlimited | Unlimited |
| Get started | Get started | Get started | Get started |
Best choice
10 USDT / period
Starter
- Concurrent pipelines
- 2
- Parallel inputs
- 2
- Results per month
- Unlimited
- Tests per day
- Unlimited
Pro
- Concurrent pipelines
- 5
- Parallel inputs
- 4
- Results per month
- Unlimited
- Tests per day
- Unlimited
Agency
- Concurrent pipelines
- 10
- Parallel inputs
- 8
- Results per month
- Unlimited
- Tests per day
- Unlimited
how it works
Your plan controls parallel processing, not the number of domains
PipelineA workflow from input to a finished result.
SlotOne pipeline that can run at the same time.
ThreadOne parallel input inside a pipeline.
OutputOne successfully created final result.
platform layers
Inside the pipeline
How the platform is wired: five layers from raw input to a published page. This is the anatomy, not the pitch — what each layer takes in and returns.
Inputs
A run can begin with keywords, search results, exact URLs, news, media or output from an earlier step.
- Keywords
- Search results
- Exact URLs
- News
- Images and video
- Previous output
Processing
Deterministic steps clean, split, combine, deduplicate and reshape data before a model sees it.
- RegExp
- Cleaning
- Dedupe
- Arrays and JSON
- Slicing
- RAG builder
AI steps
Every step has its own provider, model, prompt, temperature, token limit and output key.
- OpenAI
- Gemini
- Anthropic
- DeepSeek
- Qwen
- Compatible APIs
Control
Prompts, domain rules, variables, tests, debug output and queue state remain available for inspection.
- Prompts
- Domain rules
- Variables
- Tests
- Debug output
- Queue
Publishing
The final step sends structured fields to WordPress, the AGD CMS client or another compatible endpoint.
- WordPress
- CMS API
- Categories
- Tags
- Images
- Custom fields
pipeline example
How one keyword becomes a page
The exact steps depend on the template. A research-backed SEO workflow can follow this sequence.
- The input defines the topic, language and domain rules.
- A planning step prepares search queries and intent notes.
- Collectors load current search results and selected source pages.
- Transform steps remove noise, duplicates and oversized fragments.
- The RAG builder produces compact context with source limits.
- Writing and editing run as separate AI steps when the template requires them.
- Review rules check format, fields and claims before publication.
- Article Form maps the result and sends it to WordPress or another CMS.
templates
Pipeline templates
Importable examples cover simple generation, source-backed research, multilingual output and structured product posts. Every step remains editable after import.
comparison
From one prompt to a complete workflow
An AI article generator returns text. A content pipeline also handles the stages before and after writing.
| AI article generator | Content pipeline |
|---|---|
| One prompt | Separate research, writing, review and publishing steps |
| One model | Provider and model selected per step |
| Prompt-only context | Search, source pages and RAG context |
| Text response | Structured title, description, content and extra fields |
| Hidden processing | Visible inputs, outputs and debug data |
| Manual copy and paste | WordPress and CMS publishing through API |
| Single generation | Templates, keyword sets, queues and schedules |
| Provider token bundle | Own API keys without token markup |
faq
AI content pipeline questions
Short answers about sources, RAG, models, costs and WordPress publishing.
What is an AI content pipeline?
It is a repeatable workflow that turns an input such as a keyword or URL into structured content. The workflow can collect sources, prepare RAG context, run AI and review steps, map fields and publish the result.
How is it different from an AI article generator?
A generator mainly returns text from a prompt. A pipeline also controls source collection, processing, model choice, review, queues and delivery to WordPress or another CMS.
What does RAG add to SEO content?
RAG supplies retrieved source material before writing. It does not guarantee accuracy, but it makes the context visible and reduces dependence on unsupported model memory.
Can different models run in one workflow?
Yes. Each AI step can use its own provider and model. Planning, writing, review and JSON formatting do not need the same model.
How does WordPress publishing work?
Article Form maps title, description, content, image, tags, categories and custom fields. The mapped data is sent to WordPress through API or the AGD CMS client.
Can the pipeline produce bulk AI articles?
Yes. Keyword sets, queues, schedules and publication limits control repeated runs. Each run keeps its own sources, context, status and publishing response.
How are model costs controlled?
Cheaper models can handle planning and extraction while stronger models handle drafting or review. Supported OpenAI and Anthropic prompt caching can reduce repeated input cost by up to 90 percent, and supported Batch APIs can reduce non-urgent model cost by up to 50 percent.
Does the platform add a markup to AI tokens?
No. Providers are connected with the account owner's API keys, and token charges remain with those providers.
articles and guides
Articles and guides
Practical material on AI content pipelines, RAG for SEO, WordPress workflows and controlled bulk publishing.
What Is an AI Content Pipeline? Steps, Examples and Tools
A practical explanation of AI content pipelines: inputs, source collection, RAG, model steps, review and structured publishing.
Read →RAG for SEO Content: How to Prepare RAG-Ready Data
A practical guide to RAG for SEO: source selection, cleanup, chunking, freshness, review and a visible content workflow.
Read →WordPress AI Publishing Workflow: From Sources to Auto-Publish
A practical WordPress AI workflow for sources, RAG, review, field mapping, drafts, custom fields and controlled auto-publishing.
Read →Bulk AI Articles with WordPress Auto-Publishing
A practical workflow for bulk AI articles: keyword queues, RAG, duplicate control, review, cost limits and WordPress auto-publishing.
Read →Make vs n8n: an alternative for content publishing pipelines
Make and n8n are general automation platforms. AGD Flow is narrower and deeper for source collection, RAG, AI steps, Article Form and WordPress publishing.
Read →Jasper alternative for SEO content teams that publish at scale
When Jasper as an AI content writer is not enough: source collection, RAG context, model-per-step and WordPress auto publish in a content pipeline.
Read →Agility Writer alternative for SEO content teams
When to move from Agility Writer to a content pipeline with source collection, RAG context, model-per-step and WordPress auto publish.
Read →Byword vs Koala and Cuppa: which AI SEO writer is a real alternative?
Practical comparison of Byword, Koala and Cuppa as AI SEO writers, and where a pipeline like AGD Flow fits when sources, RAG and WordPress publishing matter.
Read →