Live MVP. Pilot programs open.

Intelligent recovery for complex airline operations

One platform that manages disruptions across aircraft, crew, and passengers. Built for airline operations control centers.

3
Recovery domains
<60s
To a recovery plan
10K+
Scenarios evaluated per disruption
The Challenge

Airline disruptions are a $60B+ annual problem

One delay spreads through aircraft, crew, and passenger systems. Current tools cannot handle the scale or the complexity.

Cascading Disruptions

A single delayed flight triggers a chain reaction across aircraft, crew, and passenger systems. Manual intervention cannot keep pace.

Fragmented Tools

Operations teams juggle disconnected systems for crew scheduling, aircraft routing, and passenger rebooking. Nobody sees the full picture when a recovery decision is needed.

Human Cognitive Limits

Operators face thousands of interdependent variables under time pressure. No person can evaluate every option while a disruption unfolds.

45%
of delays cascade to multiple flights
3.5hrs
average recovery time per major disruption
23%
of operational costs tied to irregular ops
The Solution

AURA: AI Unified Recovery Alliance

AURA is an enterprise AI platform for airline operations control centers. It predicts, mitigates, and recovers flight disruptions across aircraft, crew, and passengers at the same time.

Unified Recovery Platform

Brings aircraft, crew, and passenger recovery into a single system.

Multi-Agent Decision Making

Autonomous agents collaborate to evaluate thousands of recovery options at once.

AI Modeling

AI models forecast how a disruption will spread and select recovery actions in real time.

Auditable Consensus

A distributed ledger records every decision, so each one is traceable and explainable.

AURA ENGINE
AURA OS
Active
Aircraft

Fleet Management

Crew

Personnel Management

Passenger

Booking Management

Recovery Plan

Multi-domain solution generated

Ready
How It Works

From disruption to recovery in seconds

AURA takes each disruption through five stages, from first detection to an executed recovery plan.

01

Detect Disruption

Real-time monitoring flags operational anomalies the moment they occur: weather delays, mechanical issues, crew timeouts.

02

Forecast Cascade

Predictive models show how the disruption will spread across flights, crew assignments, and passenger itineraries.

03

Evaluate Alternatives

Multi-agent systems explore recovery scenarios and weigh operational constraints against business impact.

04

Recommend Actions

AURA recommends the best overall recovery plan with clear rationale, costs, and confidence scores.

05

Support Execution

Operations teams execute with AI-assisted guidance, live updates, and automated stakeholder communications.

Platform Modules

Three domains, one unified solution

AURA makes recovery decisions across all three domains at once, so a fix in one place does not create a problem in another.

Aircraft Recovery

Optimize aircraft routing and scheduling to minimize downline delays. AURA considers maintenance requirements, airport curfews, and fleet utilization.

Crew Recovery

Ensure legal, fair, and efficient crew assignments during disruptions. Balance duty time limits, rest requirements, and qualifications.

Passenger Recovery

Minimize passenger impact through intelligent rebooking and proactive communication. Prioritize connections and high-value travelers.

Legacy systems optimize each domain in isolation. AURA optimizes the whole operation.

Technology

Enterprise-grade AI architecture

AURA pairs machine learning with distributed systems engineering. The result is recovery guidance that is reliable, explainable, and scalable.

Research Foundation

Built from a Purdue Ph.D. dissertation on airline disruption management. Validated with real operational data from a major U.S. carrier.

Multiple AI Models

Predictive and prescriptive models trained on historical flight data forecast how a disruption will spread and what it will cost.

Decentralized Multi-Agent System

Autonomous agents represent the aircraft, crew, and passenger domains. They reach recovery decisions together through consensus protocols.

Distributed Ledger-Based Auditability

Every decision is recorded on an immutable ledger. Regulators and analysts can trace each one after the event.

Technical Specifications

Response Time
for recovery recommendations
< 60s
Solution Space
scenarios evaluated per disruption
10K+
Integration
architecture for existing systems
API-first
Deployment
flexible deployment options
Cloud/On-prem
SOC 2 ReadyGDPR Compliant
About Atreus

Intelligent systems for operational resilience

Atreus builds AI systems that help complex organizations predict, adapt to, and recover from operational disruptions.

AURA: Our Flagship Product

The first enterprise-grade AI platform for collaborative airline disruption management.

Research-to-Product Journey

The platform grew from academic research into a deployed MVP, validated with real airline data.

Beyond Aviation

The same approach applies to any industry that faces complex operational disruptions.

Founder & CEO
Kolawole Ogunsina - Founder & CEO

Dr. Kolawole Ogunsina

Ph.D. in Aerospace Engineering

Purdue University

Our founder spent years in research and industry roles in operations recovery and disruption management at multiple U.S. airlines. His award-winning Ph.D. dissertation that became AURA was developed and validated with real operational data from a major U.S. carrier.

Research Focus

Airline OperationsDecentralized AIMulti-Agent SystemsOperations Research
Get Started

Ready to transform your disruption recovery?

Join the pilot program and see how AURA reduces recovery time, cost, and passenger disruption.

Enterprise readyMVP deployedPilot programs open