If you've followed crypto Telegram for more than a week you know the noise problem: every channel claims alpha, most of it is paid shilling or recycled crypto-Twitter screenshots, and the signal-to-noise gets worse during a bull market. This is how we filter it.
What "signal" actually is
Signal is information that meaningfully moves your edge before the rest of the market sees it. By that definition, a screenshot of a 10-hour-old CT thread is noise — the trade is already over. A coordinated mention of a low-cap token across three uncorrelated channels in 30 minutes? That's signal, even if every individual message reads like shilling.
The AI filter
Pulsentric runs every Telegram message through GPT-4o-mini with a prompt that scores: sentiment (-1 to 1), urgency (1-5), confidence, and a deception flag for sarcasm/shilling. The deception flag is the one that does the heavy lifting — a sarcastic "haha to the moon" should score sentiment near 0, not +0.9.
Cross-channel correlation
Single-channel sentiment is interesting; multi-channel sentiment correlated within a 30-minute window is actionable. We aggregate per-token sentiment across the monitored channel set and surface unusual concentration on the dashboard. A token that goes from no mentions to 4 channels in 20 minutes triggers a divergence alert if price hasn't moved yet.
What we don't do
We don't sell channel access. We don't republish your private group's messages. The list of monitored channels is curated and skewed toward public alpha groups — DM-only paid groups are out of scope by design (and ethics).
The AI sentiment + cross-channel correlation are the same engine that powers Live Pulse on the home page (delayed 1h on Free tier, real-time on Pro). The filter is the product.