We built an autonomous content engine, powered by AI agents and orchestrated through n8n, that works like a full content team on autopilot.

Solution

Current solution
We built an AI content engine on n8n that connects models, APIs, and publishing tools into one flow. It automatically:
Collects relevant info from the web.
Summarizes it into clear insights.
Generates ready-to-publish content.
Posts it directly to the site or socials.


Key features & benefits


Turns any topic into clear insights within minutes using built-in search and summarization.
→ Research done in 5 min instead of 3–4 hours.

Fully autonomous research cycle

AI trained on brand tone guidelines ensures every post matches company style and SEO goals.
→ Human-level quality & automated consistency.


Consistent, on-brand AI content


Articles are automatically uploaded to WordPress, LinkedIn, and X with formatting and hashtags handled by AI.
→ ~30 minutes saved per post.

One-click publication & cross-posting

1) Topic trigger
A content strategist adds a new keyword or topic (e.g., “AI in healthcare”) to a Google Sheet 
or Notion database.
n8n detects the new entry and triggers the research pipeline automatically.

2) Web research & data collection
n8n queries search APIs (Google Custom Search, News API, or SerpAPI) and optionally scrapes the top 5–10 relevant articles.
Then it extracts titles, URLs, and article bodies for processing.


How it works

3) The scraped data goes to 
an AI summarization agent (GPT-4o, Claude 3.5, or Gemini).
It identifies key statistics, emerging trends, and expert opinions to produce a structured research brief containing core takeaways and citations.

4) AI content generation
n8n hands the research brief to 
an AI writer to produce 
a SEO-optimized article or newsletter in the brand voice.
Tone, format, and target audience are configurable via n8n variables (e.g., “friendly tone" etc.) 


5) Publication & distribution
n8n automatically uploads the final draft to WordPress, Medium, or LinkedIn via API.
It optionally posts snippets or threads on Twitter/X to amplify reach.
The workflow logs publication details and analytics data for performance tracking.
6) Reporting
Each completed article is logged in Airtable/Notion with topic, summary, publish date, engagement metrics details.
Finally, n8n sends a weekly report to the marketing team via Slack.



Automation platform:
n8n (cloud or self-hosted)

AI models:
GPT-4o, Claude 3.5, Gemini 1.5 Pro

Research & data sources:
SerpAPI, Google Custom Search, News API

Storage & tracking:
Notion / Airtable

Publishing:
WordPress API, LinkedIn API, Twitter API


Tech Stack


Research time per topic improvement: -95%
Before: ~3–4 hours
After: < 10 minutes

Content production capacity Improvement: +300%
Before: 4–5 posts/week
After: 15–20 posts/week

Cost per article improvement: -83%
Before: ~$120 (writer time)
After: ~$20 (API + review)

Engagement growth (avg.):
+40% more traffic

Brand consistency improvement: +25% perceived quality




Results

Content teams face the same struggle over 
and over:
Time-consuming research.
Inconsistent quality. 
Pressure to publish regularly.

That was exactly the case for our client, 
a B2B SaaS company producing blogs, newsletters, and LinkedIn posts every week. Their writers spent hours gathering data, summarizing sources, and drafting everything by hand.


Background

Autonomous Research & Content Generation Pipeline

Innowise Sp. z o.o

That was a really great and exciting experience, We built an autonomous content engine, powered by AI agents and orchestrated through n8n, that works like a full content team on autopilot.

Anonymous

At Innowise we believe in the primacy and supremacy of human rights, ethics, and international norms. Thus, our software development company rejects and condemns any form of discrimination, be it racial, gender, religion, or any other oppression. We support diversity, freedom of expression, privacy, welfare, and human rights of all employees. 


Innowise Sp. z o.o

About

Challenge, approach, and impact

Background

How we built

Testimonials

Team structure

Client team

Alex

Agency team

1 x AI Solution Architect (Tech Lead)

1 x Senior AI/ML engineer

1 x Senior Backend Engineer

1 x DevOps / MLOps

1 x QA Engineer

1 x Business Analyst

1 x Project Manager

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