Automated media: up to 30 news stories a day with 0 in-house editors
The client was launching a media outlet in Russia from scratch — no website, no brand, no processes — against market leaders with large newsrooms. We built the brand and an automated newsroom: 25 federal sources, ChatGPT filtering, AI rewrite and auto-publishing to the website, Telegram and social media.
| Sheet | 3.7 · “Cases” series |
| Project | Automated media |
| Industry | Digital media |
| Author | EDEMIUM |
| Status | Live · metrics accumulating |
Where the client started
How to enter the market against large newsrooms
A news outlet runs on volume and speed: market leaders publish dozens of stories a day with entire newsrooms behind them. The classic way into the niche hinges on an expensive editorial team — writers, editors, publishers.
The project, meanwhile, was starting from scratch: no website, no brand, no established processes. Building all of that while hiring and paying for a newsroom in parallel meant losing on economics before the first story.
The bet was different: build the newsroom out of algorithms. People set the rules and watch the system, while the routine — parsing, selection, rewriting, publishing — runs on a pipeline.
What we built
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01 · BRAND
Media outlet built from scratch
We developed the outlet's brand — logo, palette, typography — and a website to match. The project got a face and a platform before its first editorial hire on the payroll.
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02 · PIPELINE
Parsing, filtering and rewriting
The pipeline automatically parses 25 federal news sources. ChatGPT filters and enriches the content, then AI rewrites each piece for SEO uniqueness.
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03 · DISTRIBUTION
Auto-publishing and analytics
Finished pieces are published automatically to the website, Telegram and social media. Yandex.Metrica and Google Analytics track traffic and audience behavior.
Results in numbers
- News stories a day
- up to 30 produced by the pipeline
- Sources
- 25 federal news outlets
- In-house editors
- 0 the routine runs on a pipeline
- Traffic
- — recently launched, metrics accumulating
| Metric | Before | After |
|---|---|---|
| News stories a day | — | up to 30 |
| Content sources | — | 25 federal, auto-parsed |
| In-house editors | — | 0 |
| Website and brand | from scratch | logo · palette · typography · website |
| Publishing | — | auto: website · Telegram · social |
| SEO uniqueness | — | AI rewrite of every piece |
| Traffic | — | metrics accumulating |
Timeline and status
The project launched recently: the pipeline runs in automatic mode, publishing up to 30 news stories a day to the website, Telegram and social media — with zero in-house editors.
Traffic metrics are accumulating now: Yandex.Metrica and Google Analytics collect the data used to fine-tune topic selection and distribution.
| Status | Live · metrics accumulating |
| Capacity | Up to 30 news stories a day |
| Headcount | 0 editors |
| Exit point | Pilot KPI check: target hit → scale |
I want the same for my media
Start with an automation roadmap: in 14 days we'll show which content pipeline can be built for your niche and how much manual work it removes.