Projects using TradingView in IndiaProjects using TradingView in IndiaHow do you get TradingView alerts into Telegram in under 2 seconds, 24/7, without losing or doubling a signal? The pipeline is easy to describe and hard to keep alive. Four traps decide it.
The shape: TradingView fires a webhook, Make.com catches it, formats the message the way the channel wants it, and posts it. Capture to post in under 2 seconds, around the clock, no human in the loop. That is the scenario in the image, running for a registered research analyst since 2025.
1. The 3-second window. TradingView gives a webhook receiver about 3 seconds to respond. A slow receiver loses the alert and nothing anywhere tells you. Fix: acknowledge instantly, process afterwards, never inline.
2. Telegram's rate cap. A channel takes roughly 20 messages a minute. One volatile candle across several symbols can fire more than that, and the extras vanish silently. Fix: a per-channel queue that preserves order and releases under the cap.
3. Duplicates. Retries and repeated triggers post the same signal twice unless every alert carries a dedupe key. Two identical entries in a row is how a channel loses trust in one afternoon. Fix: a key built from symbol, signal and bar time, checked before every send.
4. Silent death. The worst failure is the pipeline stopping while you assume it is posting. Fix: every run logged, every failure alerting you on a separate channel within seconds, and a heartbeat so silence itself raises an alarm.
One more for Indian channels: if the channel belongs to a SEBI-registered adviser, promotional messages need the registration number leading the message and you need retrievable send records. That is a formatting and logging problem, so the pipeline handles it.
Branded alert images instead of plain text are the same pipeline with one extra step: an image engine lays the signal over a base card by URL, so every alert ships as a picture. That build is its own case study on my profile.
The full case study is on my profile, and the delivered version (I install it on your Make.com account, with your templates, queue, dedupe, alerting and a send log) is the TradingView product on my services page.
Prem Patel, Nex Automations. Make.com Level 5 certified, official Make partner, Zapier Certified Expert. Developed a fully automated trading system for MetaTrader 5 (MT5) that executes trades based on validated multi-indicator signals. The system integrates TradingView-generated signals with a Python-based processing engine, which evaluates multiple technical conditions before triggering precise trade execution.
The Expert Advisor (EA) is designed with advanced trade logic, risk management, and real-time execution capabilities. It ensures consistent performance by removing emotional decision-making and strictly following predefined rules.
Key features include:
ā¢ Automated trade execution on MT5 (buy/sell orders)
ā¢ Integration with external signal sources (TradingView via webhook)
ā¢ Multi-indicator validation (RSI, EMA, ADX, Volume, etc.)
ā¢ Built-in risk management (lot sizing, SL/TP control)
ā¢ Real-time processing with minimal latency
ā¢ Fully customizable strategy logic
This system enables traders to automate their strategies end-to-end ā from signal generation to execution ā ensuring speed, accuracy, and consistency in live market conditions. Engineered a high-performance Python-based trading signal engine designed to generate precise and reliable trade signals using multi-indicator confluence logic. The system evaluates over 12 technical indicators including RSI, EMA, ADX, Volume, and trend-based conditions to identify strong market opportunities while effectively filtering out noise and false signals.
The architecture is built to process real-time market data, validate multiple conditions simultaneously, and trigger only high-probability trade setups. This significantly improves signal accuracy and reduces unnecessary trades.
Key capabilities include:
ā¢ Multi-indicator confluence engine (12+ conditions)
ā¢ Real-time signal processing and validation
ā¢ False signal reduction using layered logic
ā¢ Scalable architecture for integration with trading APIs
ā¢ Seamless compatibility with automated execution systems (webhooks, APIs)
This system can be integrated with platforms like TradingView, Tradovate, or custom trading environments to enable fully automated trading workflows ā from signal generation to execution.
Designed for traders and firms looking to achieve consistent, rule-based, and emotion-free trading through intelligent automation. 
