ProjectsWorkflow Automation Systems
Internal Automation / Demo Build

Telegram Release Notifier

An automation that detects new publication updates and sends clean Telegram alerts so new releases are easier to track without manual checking.

Category
Workflow Automation Systems
Classification
Internal Automation / Demo Build
Focus
Update Detection & Alerts
Automation Flow
INTERNAL AUTOMATION — DEMO BUILD
Update to alert
Source update
New item appears
Detection
Checked on interval
Format message
Clean Telegram layout
Send alert
Delivered instantly
Log result
Recorded, deduped
Sample alert preview
New update detected
A new update was just found from a tracked source. Tap to view details.
Sent automatically · just now
Telegram AutomationUpdate DetectionDuplicate PreventionStatus Logging
How It Was Built

Four steps from manual checking to automatic alerts.

01
Mapped the source pattern
Identified how and when new updates typically appear so detection could run on a reliable interval.
02
Built detection logic
Set up scheduled checks that compare the latest state against what was already seen, flagging only genuinely new items.
03
Connected Telegram delivery
Wired detection results into a formatted Telegram message and delivery step, with duplicate prevention built in.
04
Added logging & fallback
Logged every alert sent and kept a manual check path available in case the automated check ever misses something.
Context

What this was built to solve.

Keeping up with new updates from a tracked source meant checking manually, over and over, with no guarantee of catching a release right away. This automation was built to watch for new updates and deliver a clean, immediate Telegram alert instead.
Outcome
Reduced manual checking, faster awareness of new updates, and a cleaner notification flow built on reusable automation logic.
Internal Automation disclosure: This is an internal automation built for private use, shown here as an anonymized demo build. No fandom names, source website names, private source links or accounts, specific creators, real private titles, or public community identifiers are shown — all labels are representative sample text.
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