Edity Flow scans thousands of news articles around the clock, finds the stories worth pursuing and turns them into ready-to-edit story cards. Less time searching, more room to think in new directions and be more of the newsroom you want to be.
Thursday 14 August
8 opportunities from 8,000 headlines across 11 countries.
The pension giant is selling all its offices: the number that explains why
Anna Lindkvist · 3 sources
The power bill cut in half: the households that switched in time
Jonas Berg · 4 sources
The chip shortage is back: three industries that feel it first
Sara Holm · 3 sources
Rents in Europe's big cities are turning: the map that points at the next city
Erik Dahl · 2 sources
The coffee chain that locked its price: the maths behind the promise
Maja Ek · 3 sources
The solar park nobody wanted became the town's best deal
Lisa Ström · 2 sources
Overview of the program
Every morning, thousands of stories compete for your newsroom’s attention. Someone has to find them, make sense of them and decide which ones are worth pursuing.
The problem is there’s never enough time to make sense of it all.
Edity Flow gives your newsroom a head start. It works through the noise overnight, so your team can start the day with the stories and opportunities that matter most.
One night’s flow, one morning’s briefing.
A fully agentic workflow that knows how your publication works: who your writers are, their tone of voice, the news you focus on and the angles you take. Based on that, it finds the stories and generates drafts, ready for your team to edit and publish.
Edity Flow keeps watch across the news sources and markets that matter to you, spotting new stories, emerging trends and signals worth paying attention to.
Every story is evaluated against your editorial model, while related signals from other sources are connected to reveal what’s gaining momentum.
The strongest opportunities are ranked by relevance and matched with the right writer on your staff.
The best angles become ready-to-edit story cards, with the angle, sources, headline suggestions, ideal publishing window and a first draft.
Angle, sources, headline suggestions, timing, a first draft and a suggested writer. Everything you need to take the story forward.
The editor sends the card straight to the writer, with their own edits to the draft if they want.
One click rates the card. Every answer adjusts how the next morning’s cards are chosen.
The pension giant is selling all its offices: the number that explains why
Alternative headline: The office crash nobody talks about, until now
Trending in Germany and the UK, untouched in your market. Your readers see the empty offices every day.
Anna Lindkvist
Publish before noon
Saved. The model adjusts.
We interview your editorial team to understand how you work: what you cover, who you write for, what makes a story worth pursuing and how you want it told.
We turn that knowledge into a system that works your way, gets smarter with every story and gives your team more time to focus on the work only you can do.
Your editorial model
Built around what matters to your newsroom.
Your newsroom
Another newsroom
The same story can score very differently, because every newsroom values different things.
Two views, one purpose. The Radar shows every story moving across your markets in real time. The Watchlist follows the areas you want to keep an eye on: add a company or topic, and Edity Flow tells you when something starts moving.
Every dot is a story moving in your markets right now.
The areas you follow. Add anything you want, and remove it whenever you want.
We build and configure your system in 5 to 6 working days.
We interview your editorial leadership
We build your scoring model, connect your sources and define your editorial voice
Your system is ready. Your team gets access and can start using it
We train your newsroom and hand over the system
Your first month is free. Use it in your newsroom before deciding whether to continue.
Starting after your free first month.
Morning briefing, every day
Radar and Watchlist, live throughout the day
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Support, updates and ongoing improvements
Book thirty minutes. We’ll look at how your newsroom works, what you’re trying to achieve, and whether Edity Flow fits.
A real card from a live morning briefing. Names and newsroom details anonymised.
Alternative headline: Big tech chased his farmland for years. The 86-year-old chose the land over the fortune
The data center rush is the AI era’s great land grab, and this story gives it a human face nobody in your market has taken. You own the translation: the same hunt for land, power and water is happening at home, and the question of what a piece of farmland is really worth lands straight in the national debate.
Trending in the US and picked up by local TV across the country. David versus Goliath plus a value conflict: one person saying no to the money everyone else is chasing.
FREE. Zero hits on data centers, server halls or land deals in your market.
The small business owner, the senior investor, the matriarch. A broad emotional story with an economic core.
Viral in the last 24 hours, still unclaimed in your market. Publish today, weekend reading with a long life.
Anna Lindkvist
Low to medium. Backed by the township and several TV stations. Verify the amounts before publishing.
261 acres of fields, a barn where he milked cows for 51 years, and an offer of more than 15 million dollars. 86-year-old Mervin Raudabaugh in Pennsylvania said no. [FACT CHECK: 261 acres = roughly 106 hectares, pick one unit and stay consistent.]
The data center companies offered 60,000 dollars per acre for his land in Silver Spring Township, reports the trade paper Lancaster Farming. The deal covered three neighbouring properties as well and would have turned the fields into server halls.
“I wasn’t interested in destroying my farms. That was the whole thing. It really wasn’t about the money”, Raudabaugh tells TV station Local 12.
HE CHOSE THE CHEAP ROAD
Instead of selling, Raudabaugh signed away the development rights to the land for a fraction of the offer: roughly 7,200 dollars per acre plus an extra 2,500 dollars per acre, according to the township’s own announcement. [FACT CHECK: ABC27 puts the total at roughly 2 million dollars, reconcile against the township’s numbers.]
The land can still be sold one day, but only to someone who keeps it as farmland. The Lancaster Farmland Trust holds and monitors the easement.
The model is unusual even in the US: residents of Silver Spring Township voted in 2013 to fund the land protection through a local tax, roughly 120 dollars per household per year, according to the township.
“THESE PEOPLE HAVE HOUNDED THE LIFE OUT OF ME”
The backdrop is the AI boom’s hunt for land. Data center brokers have courted landowners in the area for years.
“These people have hounded the life out of me”, Raudabaugh says in the township’s announcement.
His worry goes beyond his own farm: the traffic, the groundwater and the wildlife as the halls grow, reports Local 12.
AND AT HOME?
The same land rush is under way here. Tech giants are building and planning server halls across the country, and municipalities compete for them with cheap power and fast permits.
[FACT CHECK: the local section needs its own research. Pull fresh examples of data center projects and land conflicts, and put the question to the farmers’ association: what happens to the price of farmland when the data center companies start bidding?]
For Raudabaugh the matter is simple. His mother died in his arms in the barn on the farm. Some things are not for sale.
FACT BOX (source per claim)
• The 15 million dollar offer, 60,000 dollars per acre, the neighbouring properties: Lancaster Farming + ABC27
• The preservation payment, the tax model, the 2013 referendum: Silver Spring Township
• The quotes: Local 12 + the township’s announcement
• 51 years as a dairy farmer, his mother: Local 12
[IMAGE: elderly farmer in front of farmland, alternatively a server hall against fields, at least 1200 px wide]
First draft in the house voice, around 450 words. Every claim carries a linked source. The editor edits, the newsroom decides.
Saved. The model adjusts.