You own the blog, the newsletter and four social channels, and the calendar is always behind.
You know the business better than any writer, but a post still eats a whole evening.
Ten brand voices, ten CMSs and a repurposing routine that never gets done.
Hundreds of product descriptions and landing pages that must stay consistent and findable.
Numbers from the latest content marketing surveys — most teams have the tools, but not a process that uses them every week.
of B2B marketers name lack of resources as their biggest content challenge.
Content Marketing Institute, 2025 ↗is the average time to write one blog post — down from a peak of 4h 10m in 2022, but still half a working day.
Orbit Media, 2026 ↗of teams have built generative AI into their daily process; 54% still use it as ad hoc experiments.
Content Marketing Institute, 2025 ↗of marketers substantially rewrite or redo AI-generated text; only 7% publish it without edits.
HubSpot, State of AI for Marketers 2025 ↗of content marketers worry about accuracy and factual errors in AI text; 63% fear a lack of originality.
Orbit Media ↗of bloggers report strong results from their blog — a historic low.
Orbit Media, 2026 ↗Put your monthly volume into the calculator and see hours and dollars.
Content automation is a workflow that takes the repeatable steps of content marketing — keyword research, briefs, first drafts, fact checks, CMS layout, meta tags, repurposing and reporting — and runs them without a person copying text between tools. An average blog post still takes more than three hours to write, and most of that time is not spent on ideas. It goes to collecting research, formatting and cutting the same piece into five formats. That is the part a content automation flow removes.
We build marketing content automation around the tools you already use rather than a new platform. Approved topics in your calendar trigger research through Ahrefs or Semrush, a brief in Google Docs, a draft written by a language model from your style guide and knowledge base, and an automatic check of every claim. The editor sees flagged sentences, not a wall of text. Clean articles are published to WordPress or HubSpot with everything filled in, rewritten for each social channel and queued in Buffer or your email tool.
When you automate content marketing this way, the team stops drafting and starts editing, which is where their judgement matters. Output goes up without hiring, every post gets social and email coverage instead of the ones someone had time for, and a monthly digest from GA4 and Search Console tells you what actually worked. Strategy, expert opinion and the final word before publishing stay with people.
The run path of one article. Every piece travels it on its own; a person approves the brief and the final draft before anything goes live.
A row in the content calendar (Notion, Google Sheets or Airtable) switches to “approved” and starts the run for that topic.
Fetches the top-ranking pages, related questions and search volume from Ahrefs, Semrush or DataForSEO, plus your own GA4 and Search Console numbers.
A language model turns research into a brief: angle, outline, target questions, internal links and the facts that must be included.
The brief lands in Google Docs or Notion with a comment to the marketing lead. Nothing is drafted until someone says yes.
Pulls the style guide, banned phrases, product facts and past high-performing posts from your knowledge base into the prompt.
Writes the article in your brand voice from the approved brief, with sources named inline and placeholders for expert quotes.
Each statistic and claim is checked against the named source; anything unverified is flagged in the margin for the editor.
Sends the draft to the editor in Slack with the flags listed. Edits are made in the document, not in a chat window.
Produces a featured image and alt text through an image API or a Canva template, in your brand colours.
Creates the post in WordPress or HubSpot through the API with title, meta description, slug, categories and internal links filled in.
For each channel in your list, a language model rewrites the article into a LinkedIn post, an X thread, an Instagram caption and a newsletter block.
Queues the versions in Buffer or Hootsuite and the email block in Mailchimp or Klaviyo on your posting calendar.
Reads GA4 and Search Console, lists what grew and what stalled and sends a summary with suggested next topics to Slack.
Typical minutes per article in a small marketing team. Your own numbers go into the calculator below.
Based on 3 h 15 min by hand and 30 min with the flow per item, from the table above.
The flow researches, drafts, checks and distributes. People keep the decisions that make content worth reading.
Positioning, what to write about and what to leave alone stays with the marketing lead.
Nothing is published until an editor has read it and cleared the flagged claims.
Case studies, customer numbers and first-hand experience come from your people.
Medical, financial and legal content is approved by someone qualified before it goes live.
A person reads the monthly digest and decides what to double down on and what to stop.
The style guide is edited by people; the model only follows it.
Flip a switch to hand a step to the flow or take it back.
Benchmarks from Orbit Media’s 2026 survey of 1,042 content marketers and the Content Marketing Institute’s 2025 B2B research: the teams that get results are the ones that have made AI part of a repeatable weekly process, not an experiment.
We map the process as it runs today, count the minutes and agree what the flow must never do on its own.
A working flow on your real data, in a sandbox. You see every run and every exception.
Edge cases, approvals and alerts, then the switch-over — with the old way kept as a fallback.
Monitoring, fixes when a vendor changes a format, and a monthly report of hours saved.
You can automate the routine: research, briefs, drafts, publishing and repurposing. We keep two approval points — the brief and the final draft — because that is where quality is decided. Fully unattended blogs read like it, and the numbers show they do not perform.
The model is given your style guide, banned phrases, product facts and examples of your best posts on every run, and the draft is scored against them before an editor sees it. Over time, edits your team makes feed back into the examples.
Google’s guidance is about quality and usefulness, not about which tool wrote the text. Thin, generic pages lose either way. The flow is built to add your data, expert input and real sources to every piece, which is what ranks.
Every claim in a draft is checked by code against a named source and flagged if it cannot be verified. The final call stays with your editor; the flow makes sure they see the flags instead of reading 1,500 words looking for them.
That depends on how many approvals your team can handle, since drafting is no longer the bottleneck. Teams that published two posts a month commonly move to eight or ten plus full social coverage without hiring.
After publishing, a language model rewrites the piece for each channel in its own format and length, and the versions are queued in Buffer, Hootsuite or your email tool. You see them in one review before they go out.
Your knowledge base stays in your own account, and the model can run through an API with no training on your data or on a local server. Every prompt and output is logged, so you can see exactly what left your systems.
Describe it in two sentences — we reply within a day with a workflow sketch.
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