01 / FLIGHT AI
The operation in one view
Current flight operations application with illustrative flight, fuel, timing, and aircraft records.
FLIGHT AI · Flight operations intelligence
Make flight data useful to the operation.
Bring flight records, measured performance, return documents, and operational signals into one workspace. FLIGHT AI helps your team investigate the difference between the plan and what happened.
Inside FLIGHT AI
See the work, from start to finish.
Explore the current product interface with demonstration data. Open any screenshot for a closer look.
02 / FLIGHT AI
From totals to the reason behind them
Compare planned and measured fuel and inspect efficiency trends. All figures shown are sample data.
03 / FLIGHT AI
Read the trend behind the totals
The same operational workspace, with illustrative delay observations and aircraft fuel totals.
Capabilities
The details that keep work moving.
Flight records, fuel intelligence, document extraction, and operational forecasts.
Connect the flight record
Synchronize historical and recently modified ForeFlight Dispatch records. Inspect flight, aircraft, crew, planned fuel, weight, and operational timing information together.
Compare the plan with measured performance
Analyze planned and actual fuel on matching eligible flights. Explore aircraft and route differences using measured burn, time, distance, and explicit data gaps.
Separate taxi behavior by aircraft type
Review measured taxi-out fuel by station and aircraft type. Keep E190 and E175 results separate, with sample counts and monthly breakdowns.
Understand schedule performance
Compare planned block time with recorded OOOI events. Explore departure performance, taxi time, route patterns, and delay trends using defined observation populations.
Read the documents behind the flight
Classify return documents and extract structured fields from load sheets, fuel slips, logbooks, NavLogs, and takeoff or landing performance records. Inspect extracted values alongside the source.
Reconcile zero fuel weight
Compare available ZFW information across the flight record and return documents. Surface discrepancies for review instead of silently treating extracted fields as authoritative.
Examine forecasts and anomalies
Review fuel predictions, departure delay risk, operational anomaly signals, and model status. Stored backtest metrics expose how trained models compare with historical observations and planning baselines.
Keep operational context close
Use live tracking, network weather views, ACARS messages, crew records, passenger analytics, and sync status as connected views of the operation.
Applied AI
AI that starts with the flight record.
Document extraction and trained models address concrete analytical jobs. The interface keeps observations, predictions, and missing data distinguishable.
Vision extracts structured fields
Configured vision models read supported return documents into typed fields. Absent or illegible values remain unavailable for the review workflow.
Models are trained and backtested
Fuel and delay models use historical flight data with a time-forward holdout. Anomaly signals retain feature context so analysts can examine the reasons behind a flag.
Use the right method for the question
Taxi allowances use observed medians and percentiles. They are descriptive statistics rather than a claim of machine-learning prediction.
Evaluate FLIGHT AI
Make the next step measurable.
Agree a representative sample and a baseline from your current process. These are proposed evaluation measures, not published performance results.
Bring a representative example
Representative return documents and a held-out period of flight records.
Inspect the complete workflow
Check extracted fields against reviewed values and forecasts against a simple baseline.
Compare with your baseline
Field accuracy; missing-data coverage; forecast error; reviewer correction time.
Questions & answers
Before you book a demo.
Does FLIGHT AI operate independently of Aurora?
Yes. The flight operations application has its own records, dashboard, authentication, data synchronization, and analytics. Aurora is not required for those workflows.
What does the AI actually do?
Configured vision models classify return documents and extract supported fields. Trained models estimate fuel burn and departure delay risk, while anomaly detection flags unusual operational observations for review.
Does FLIGHT AI generate an approved dispatch release?
No. FLIGHT AI provides operational records, analysis, document review, and decision support. Authorized personnel retain responsibility for approved planning systems, release decisions, and required calculations.
How are planned and actual fuel compared?
The application compares positive plans and valid measured burn on matching eligible flights. It distinguishes measured consumption, planning values, and missing observations.
See FLIGHT AI in action
Request a demo Start with your workflow.
A focused walkthrough, with the people and decisions that matter to your team.