Omnius · n8n Lab

The problem

Omnius, a B2B SEO & AI Search marketing agency, needed to scale content production for multiple clients, handling research, ideation, drafting, and distribution across various platforms while maintaining quality and brand voice.

What was deployed

Vendor

n8n Lab

Products

n8n, OpenAI GPT-4, DALL-E, YouTube API, Apify, WordPress API, LinkedIn API, Google Docs

Models

GPT-4, DALL-E

Technique

LLM

Build or buy

Bought and customised

Deployment

Custom build

Data used

YouTube and X content

What changed

Each row is quoted from the source. Figures we could not find on the page in those words are marked — they are kept, not deleted, so you can judge them.

Difficulties and limits

• Multi-Client Research Load: each client operates in a different niche, so research for one does not apply to another
• Real-Time Relevance: the best topics have a short shelf life; trending conversations need immediate action
• Format Intelligence: not just what to write, but how — a topic might be a blog post for one platform, a carousel for another
• The Expertise Asymmetry: strategists are SEO experts, not industry experts, and need to get up to speed on niche topics quickly
• Platform-Specific Adaptation: manually reformatting content for LinkedIn, WordPress, and X is a bottleneck
• The Approval Bottleneck: email chains and document hunting for approvals slow down publishing
• Visual Asset Creation: manual design requests create a queue and add delays
• Distribution Fragmentation: logging into multiple platforms to publish is inefficient

• AI drafts still require human review to ensure brand voice, accuracy, and strategic alignment before publishing

Sources

• n8nlab.io — vendor self-report