Collection yields raw material: pages, paragraphs, numbers. A human cannot read that, so the AI stands between collection and you. Its job is to turn hundreds of items into short, clear facts — and to stay honestly silent where it knows nothing.
Why AI
- Shorter. Instead of a page of text — two sentences and a link to the source.
- Clearer. Instead of “−25.6%” — “the price fell by a quarter”.
- More connected. Material about one happening gathers into one story instead of arriving in scatter.
- More discerning. The materiality rating separates what deserves your attention from the background.
A summary built strictly on the material
The main rule of processing: no inventions. The summary is built only from the collected material, and next to every statement stands a link to the exact quote. When there is no backing in the text, an honest note that no confirmation was found appears instead of a pretty retelling.
This matters in news: an invented phrase sounds exactly as convincing as a real one, and is discovered only when it is already too late.
The materiality rating
The rating runs on a scale from 0 to 10 and then sorts into four clear bands — “noise”, “worth knowing”, “material”, “existential”. The threshold where “material” begins is yours to set; by default the product is tuned not to send you trifles.
When a rating looks wrong, tell the agent: it will fix the rules or add a caveat. An unprocessed event is honestly marked “unscored” — there are no invented numbers in the interface.
Topics
Every item automatically gets topics from your own structure: “prices”, “supplies”, “regulation”, “our products”. Topics are then handy for filtering events and building rules: “everything about regulation — into a separate digest”.
Entities
Entities are the companies, people and products mentioned in the material. The agent keeps their list and marks the mentions: you can see how many times a competitor came up in a month, and in what context. The list is edited in words: “add this company to the list, it is our supplier”.
Stories
When one piece of news has been reprinted by ten outlets, reading ten items is pointless. The agent gathers material about one happening into a story — a page showing how the news developed.
- New — the story has just appeared; no follow-ups yet.
- Developing — new material keeps arriving.
- Fading — no new material for a long time.
- Archived — the story was closed by you or by the agent.
Translation
Material in a foreign language can be translated on request: the translation is shown next to the original, so the wording can always be checked. Translation is done on your request, not for everything at once — that keeps AI spending under control.
Confirmation by independent sources
The agent counts how many independent sites have reported one happening. The confirmation count is visible in the story, and a protection against lone news items can be built on it: a rule like “do not send until at least two different sites confirm the news” is described in the Alerts & Noise Protection section.
Your own AI provider and your own processing
Processing can not only be configured but also replaced with your own Python code:
- Any AI task can be routed to your own code — the summary, the materiality rating, the topics. Useful when things must be computed by your own rules, or without calling an external service.
- Quotas and spending accounting work the same as with ordinary models: you see how many tasks went out and how long they took.
- You can add your own facts — the code walks all the items and events and leaves its own marks, on which rules then work: “act when the code counted this specific fact”.
- Unavailable code is not replaced by someone else’s answer — the task is honestly marked as not completed.
Details — in the Custom Scripts section.
Queue, quotas and spending
Every model call is money and time, so processing goes through a queue with two limiters:
- The daily call quota — how many AI tasks are allowed per day. The quota ends loudly: the interface shows that processing has stopped and why.
- Spending accounting per task — you see how much went to summaries, how much to materiality ratings, how much to publication drafts.
When the quota is exhausted, the collected material and events stay in place — processing simply waits. Nothing is lost, and analytics shows exactly where you hit the limit.
What the AI does not do
- It does not detect the mood of a text. The function exists, but it honestly answers “not configured” instead of inventing percentages.
- It does not transcribe videos, podcasts and pictures. Such material keeps only its descriptions.
- It does not publish on its own. The AI prepares a draft, and sending happens only after your approval: Publishing.
Next → Rules