Every signal we publish is hashed into a SHA-256 chain before its outcome is known. The chain is public. If a single past call were edited, every later hash would mathematically break, and the tampering would be visible to anyone with a snapshot. That solves the single biggest problem with sourcing third-party signals: knowing the track record is real.
Manual onboarding for now. Discovery call → integration spec → API credentials. Typically 3-7 business days from first email.
Pain: Vetting external signal providers is a nightmare. The market is full of fake screenshots, deleted losing calls, and 'VIP' upsells. Your compliance team can't sign off on what it can't verify.
Fit: Our public hash chain IS the verification. Your due-diligence team can audit any past signal end-to-end before integration. Live feed, full historical record, zero hidden state.
Pain: You need verified content for paying users. Self-published signal services have no third-party validation.
Fit: Wholesale signal access scoped to your distribution. Resell as part of your bundle. We handle methodology and engineering; you handle distribution and end-user UX.
Pain: Buying alpha from anonymous signal services is a non-starter. You can't verify what's claimed. You can't size against an unverifiable edge.
Fit: The hash chain anchors the methodology. Combine our signal as one feature in your stack. Backtest history is reproducible because the published values are immutable.
Every signal is SHA-256 hash-chained at fire time before resolution. Editing any historical signal breaks every later hash. Your compliance team can recompute the chain from the public canonical strings yourself.
No cherry-picking. Every signal that fires is in the public ledger, including the losers. Your win-rate due-diligence is mathematically complete, not a screenshot collection.
Every call ships with the trend / momentum / volatility breakdown that produced it. End-users can be shown the rationale, not just the trigger.
BTC, ETH, SOL on H1 / H4 / D1. Conviction-scored 0-10 against historical outcomes. Configurable filters per integration.
Our R-Regime exit ladder (regime-aware sizing + runner trail on TP3) showed +0.82 percentage points of expectancy lift over baseline on the validation slice. Methodology is documented; results are reproducible against the public chain.
You talk directly to the person building the system. No five-layer vendor relationship. Custom payload shape, rate limit, or filter you need? Real conversation, fast turnaround.
We don’t publish list prices because no two integrations are the same. Every partnership is quoted against the things that actually move cost: how many end-users see the feed, what redistribution rights you need, and the SLA your stack requires.
Tell us about your platform and use case. We’ll come back within 1-2 business days with integration specs and next steps.
Or email support@ezath.com directly.