FPL + IGC + FTR · flight replay · deterministic analysis without AI
Dolomites: eight decisions that change a flight
See on the map where time was spent, why lift faded and what helped the pilot. This is a synthetic training example: measurements describe this example, and suggestions identify specific actions to practise.
The demo uses real FPL geometry and a synthetic replay prepared only to demonstrate Flight Analysis. It is not an output of the private Strategy Engine.
Flight Analysis
ANALYSE THIS FLIGHT WITH AI
Download a ready-to-use file and attach it to ChatGPT, Gemini, Claude or another AI model. Choose the level of detail.
QUICK AI CONSULTATION
Condensed report — Markdown (.MD)
Key flight results, task, thermals, time budget, lessons, data consistency and limitations.
Best for quick questions such as: What were my three biggest mistakes? What did I do well? What should I train next?
FULL AI ANALYSIS
Complete data package — JSON (.JSON)
Full analysis context: task and weather data, consistency checks, detected events, insights, statistics and the complete point-by-point replay. If a second-pilot comparison was loaded, its comparison result is included too.
Best for deep analysis of task execution, route choice, thermalling, glides, altitude and energy management, speed, wind and Weather Zones when available, deviations and final glide.
How do I analyse the flight with AI?
- Download AI QUICK REPORT or the FULL AI PACKAGE.
- Open ChatGPT, Gemini, Claude or another AI tool that accepts file attachments.
- Attach the downloaded .MD or .JSON file.
- Click “Copy prompt for AI” below and paste it into the conversation.
- Ask follow-up questions as needed; you do not have to copy tables from the portal manually.
Sources and consistency
Coach
Sources and consistency
FTR
Thermals and segments
| # | Time | Duration | Climb | Gain | Rating |
|---|