Inside the Agent
Pipeline
Copilot, Shield, Ghost, and Watch, in the order a transfer actually meets them, plus the API shape and latency budget behind them.
One Call, Four Agents, In Order

Four Agents, Each With One Job
Copilot — Baseline Engine
Learns a per-user behavioral baseline from day one: who they pay, when, how much, and which devices. A transfer that matches clears with zero added friction.
Shield — Six Signal Layers
Amount anomaly, new recipient, time-of-day, channel risk, narration keywords, and NIP response code. Scored and explained in plain language, inside a 200ms budget.
Ghost — Cooling Window
Routes an overridden block into a disposable holding account instead of letting the transfer clear outright, so even a fully-scammed user has a way back.
Watch — Passive Monitoring
Runs between sessions, watching for pattern drift and device changes, without adding latency to the transfer path itself.
One API Call, in Front of Every Transfer
Banks, fintechs, wallets, and gateways integrate with a single scoring endpoint. Context, device, and behavioral signals go in; a decision, a risk score, and a plain-language reason come back.
POST /v1/score
{
"transfer_id": "txn_8f2ac1",
"user_id": "usr_44210",
"amount": 150000,
"recipient": { "account_number": "0123456789", "bank_code": "058" },
"channel": "app",
"narration": "urgent help abeg"
}{
"decision": "FLAG",
"risk_score": 78,
"signals": ["new_recipient", "narration_keyword", "time_anomaly"],
"action": "ghost_hold",
"latency_ms": 142
}Fast Enough to Sit in Front of Every Transfer
Not just the risky ones. The full pipeline has to clear before the transfer does, so it’s built to a hard latency budget, not a best-effort one.
<0ms
End-to-end response time, all four agents included
0s
NIP's clearing window; Fable uses a fraction of it
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