How Domino Automates ATO Planning

Air tasking order planning across contested airspace is one of the hardest agentic AI problems in defense — and the first one that demands a full governance audit trail. See how Domino's Enterprise AI Platform powers RAPTOR, an AI-driven air operations decision support suite that plans, evaluates, and defends every course of action.

Automate ATO planning with governed agentic AI — RAPTOR's two-agent loop drafts the air tasking order and stress-tests it against threat models, fuel constraints, and airspace volumes before it ships, with every agent decision traced and every tool call logged.

Built on a production MLOps platform — compute environments are sandboxed and versioned, LLM calls route through Domino's AI gateway for centralized key management and per-call logging, and the experiment manager captures every run that informed the fuel model and threat check engine.

Full agentic ai governance from day one — a NIST AI RMF-aligned governance bundle is attached before any code is written; model registry cards auto-populate for ATO documentation; and model reproducibility is guaranteed by replaying the original hardware, packages, and parameters at any point.