How to Filter Noise Out of Your Telegram News Feed

The math of running a news channel is brutal: your sources produce a thousand messages a day, and maybe three are worth publishing. Keyword filters can't fix this — they either let the noise through or bury the signal. Here's the filtering stack that actually works.

Layer 1: AI scoring, not keywords

Every incoming message gets analyzed by AI: translated, summarized, tagged, and scored 0–100. The score balances world impact against your topics — and it's recomputed instantly when you change weights, without re-analyzing anything. Sort by score and the important stories float to the top before you read a single post.

Layer 2: positive signals — topic matching

Define the topics you care about once. Matching tags render as green chips on every card, so relevance is visible at a glance. Because the AI works on meaning (not strings), a Russian-language post about your topic still matches an English topic definition.

Layer 3: negative filtering — blocked topics

This is the layer almost no tool has. Say “I never want to see crypto” — blocked topics quarantine matching posts into a separate feed you can ignore entirely. Again, matching runs across languages: a crypto shout-out in any language lands in the same bucket.

Layer 4: structural noise removal

• Story cards collapse five posts about one event into one card.
• Duplicate hashing drops identical forwards at ingest.
• Compact mode + keyboard triage makes dismissing what's left a sub-second decision per card.

The result

Filtering isn't one feature — it's a pipeline where each layer removes a different kind of noise. What reaches you is a short, ranked, deduplicated list in your own language. That's the difference between two hours of scrolling and twenty minutes of deciding.