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Getting Started

The LogAir.ai Value Proposition

So you have the typical 52.2 year old piston-powered GA aircraft with about 500 pages of log data, ADs, SBs, 337s — much of it hand written. There are maybe 100 ADs on the engine and airframe. It’s a lot of data.

LogAir.ai is the first company to use RAG-AI to bring value to your maintenance records.

Retrieval-Augmented Generation (RAG) is a form of AI where a set of data, your log data, is used to both, “prime the pump” and control what data the AI will consider when forming an answer. This is called the RAG corpus of information.

The result are accurate answers, with citations.

Powered by a state-of-the-art AI language model with billions of parameters, this system thinks intelligently—but only within the boundaries of the data you provide. In effect, you’ve “trained” it on your own logbooks, documents, and records. Every answer it gives comes directly from that information—nothing imagined, nothing made up. Just precise, data-driven results.

We prime our bigger data sets with aircraft maintenance logbook data, all of the Airworthiness Directives on the airframe and engine(s), data from 337 Forms, and other manuals.

What we can do

If this is all foreign to you, don’t worry. You will soon see how valuable it is.

Example Queries

  • How much has this aircraft flown over the past five years?
  • Did this aircraft and engine ever sit idle for any appreciable length of time?
  • How many hours on the magnetos?
  • Has this aircraft every been in a gear up incident? Describe any extensive airframe repairs.
  • Output a table of the right engine compression values over the last several years.
  • When is the 91.411 or 91.413 inspection due?
  • What are the engine accessories last overhauled?
  • What ADs have been applied to this Aircraft?
  • What is the average oil change interval on this engine in the past?

Read the Keep Flying! blog post

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