Media and Publishing
AI Automation
A finance publisher was spending two hours every morning doing work that a well-built automation could handle in minutes.
Services
AI Workflow Automation
LLM Integration
Editorial Automation
Data Centralisation
Daily newsletters built on manual research are a common bottleneck in media and publishing. The process is repetitive, time-consuming, and hard to scale. Dataverse automated the entire pipeline from research to editorial review to distribution, cutting daily effort by ninety percent while keeping the publisher in full control.
It basically runs itself now. I spend ten minutes reviewing instead of two hours researching. The quality is consistent, the coverage is wider, and I can actually focus on the parts of the business that need my attention.
90%
Reduction in daily manual effort
10 min
Editorial review time (was 2 hours)
40+
Financial sources covered automatically
The Challenge
The publisher produced a daily finance newsletter that required extensive manual research each morning. Reviewing Bloomberg, the Financial Times, Business Insider, and other premium sources, copying excerpts, organising by company, synthesising key information, and assembling the final newsletter was a multi-hour process repeated every day. As the audience grew, the workflow became a ceiling on what the business could produce. The manual bottleneck limited output, drained time that should have gone to strategy, and made scaling impossible without hiring.
Two or more hours of manual research and curation required every morning to produce the newsletter
Coverage limited by what a single person could review in the available time
No scalable system for expanding sources, topics, or output frequency
Repetitive process leaving no time for deeper analysis or audience growth
The solution
Dataverse built a fully automated news intelligence and publishing system using n8n, SerpAPI, Tavily, GPT-4-mini, and Airtable. The workflow continuously gathered fresh financial articles from a curated list of approved domains, fetched full content where APIs returned partial results, and generated high-clarity executive summaries. Each item was enriched with structured metadata including company tags, source links, and extracted insights, then stored in Airtable as the central content database. A custom Airtable interface served as a lightweight editorial CMS where the publisher could filter content by company, approve or reject summaries, and trigger automatic newsletter assembly and distribution with a single action. Dynamic controls allowed him to update source domains, adjust keyword filters, and expand coverage without any technical dependency.
Automated research pipeline gathering and summarising articles from more than forty financial sources
GPT-4-mini generating executive-quality summaries with company tags and structured metadata
Airtable acting as the central content database and lightweight editorial CMS
One-click newsletter assembly and distribution triggered directly from the editorial interface
Dynamic controls for adjusting domains, keywords, and coverage without technical involvement