USE CASE · DATA

Data licensing.

Some partners don't want turnkey markets — they want the underlying signal. Quant funds, algorithmic trading desks, treasury hedging programs, embedded-fintech apps. Aviax licenses the raw oracle feed and historical archive separately from the markets.

What plugs in

A streaming API for live flight events and a historical archive for backtesting. The same data that drives Aviax's market layer is exposed as a structured feed: per-flight tier outcomes, timestamps, signal-evidence pointers, and the deterministic resolution record.

Integration shape

Two endpoints:

Live stream. WebSocket subscribe with filters (region, airline, airport, threshold). Receive structured events as flights ingest, score, and resolve. End-to-end signal-to-event delivery in seconds.

Historical archive. 8-year corpus of flight pattern data, available as Parquet exports for backtesting and model training. Same schema as the live feed.

Sample event payload (preview)

{
  "flight_id": "UAL1283-2026-05-07",
  "scheduled_departure": "2026-05-07T14:23:00Z",
  "scheduled_arrival": "2026-05-07T18:11:00Z",
  "outcomes": {
    "delayed_15min": true,
    "delayed_30min": true,
    "delayed_60min": false,
    "cancelled": false,
    "diverted": false
  },
  "settlement_window_close": "2026-05-07T18:41:00Z",
  "signal_attestation": "...sig..."
}

Who buys

Quant funds running aviation-correlated trades (airline equities, jet-fuel forwards, hospitality revenue cycles). Treasury desks at travel companies hedging operational delay risk. Algorithmic insurance carriers. Embedded-fintech apps building flight-aware features (rebooking, lounge access, automated compensation).

The common thread: real-time and historical signal-grade data, with a settlement-bound outcome shape that's machine-consumable.

What makes it different

Legacy flight data providers serve airline operations centers — their schema is built around crew rotation, gate management, and fuel planning. Their resolution latency is acceptable for ops decisions but unacceptable for settlement, and their outcome shape requires significant transformation before it can drive a trading or insurance signal.

Aviax's data shape is built for the consumer use case: deterministic, machine-readable, settlement-grade. Less data than legacy providers, structured to be useful immediately.

Why this is now possible

Streaming oracle infrastructure + 8-year curated archive + deterministic outcome encoding all came together in the last 18 months. The companies that need this signal previously had to build it from scratch. The category-level oracle is here.

Request pilot