Save Your Crypto Before The Next Platform Collapse
[AI-Powered Early Warning System]
Get 6-12 hours to withdraw before platforms crash or freeze. Our AI detects patterns that preceded FTX and LUNA collapses, giving you critical time to withdraw.


Your 24/7 Crypto Safety Net
Don't risk losing everything like FTX victims. Our system watches these critical areas:
Exchange & CeFi Failures
Spot bankruptcies, hacks, and liquidity crises hours before withdrawals freeze
DeFi, Wallet & Protocol Risks
Wallet vulnerabilities (Phantom, Trezor, Rabby...), firmware compromises, governance attacks, yield farm collapses, and depegging events
Regulatory & Operational Risks
Criminal investigations, mass withdrawals, regulatory crackdowns, and proof of reserve issues before they hit the news
AI-Powered Risk Detection
Sleep better at night while our AI monitors 100,000+ signals every 15 minutes across social media and on-chain data. Get instant Email & Telegram alerts when we detect patterns matching previous platform collapses.



Proof It Works
After 6 figures in the LUNA crash, I swore it wouldn’t happen again. When the Bybit hack hit, SwanWatch’s lightning-fast alert pinged me within minutes—way before the news broke. That edge let me pull my $30K out while others were still clueless.
Crypto Fund Manager
SwanWatch alerted me to the PAXG depeg from physical gold rates 2 hours before the masses knew about it. I sold my position and bought back after the 8% drop – turning what could have been a loss into a significant profit.
Investor
I’ve dissected every crash—FTX, Celsius, you name it. SwanWatch’s backtests nail the warning signs with uncanny precision. It’s a genius safety net, plain and simple.
Crypto Security Analyst
Mitigate Risks
- Ability to define custom platforms to monitor (CEX/DeFi/CeFi/Wallets/Depegs...)
- Full risk coverage: bankruptcies, hacks, bank runs, depegs, regulatory raids, executive arrests & exploits, proof of reserve issues, & more
- Instant alerts via Email + Telegram dual-channel
- 24/7 automated monitoring of Social medias and on-chain data