Case study: datasohub – AI-assisted content production in production
From research to a published post in about 7 minutes: a multi-model pipeline with a generative blog system and a data-driven frontend.
AI in production, a multi-model pipeline.
Tech stack: Multi-model architecture · AI features · Image generation
Problem
Content production was entirely manual: research, writing, posting, creating or buying imagery – time-consuming and not scalable.
My role
Concept and implementation of the generative blog system and the data-driven frontend.
Solution
LLM-assisted web search for research, a data-driven frontend with React and SQLite, and a generative blog system that produces posts including imagery.
Result
From research to a published post in around 7 minutes instead of manual hours – fully automatic via cron job on demand. Live in production at dataso.de/blog.
Takeaways
The bottleneck shifts from writing to curating: a data-driven frontend keeps the generated content consistent and maintainable. Full automation is technically possible – editorial guardrails decide the quality.