AlliedOffsets recently launched an AI Document Reader (AIDER) tool, which allows users to extract data out of project documents in a structured way to conduct bespoke analysis.
The ability to extract actionable data from documents enables users to:
In this blog, we showcase an example of how AIDER is used to extract niche data on projects, which can aid companies in conducting due diligence, project evaluation, and compare projects across their peers.
Afforestation and reforestation projects plant seedlings that sequester carbon as they grow into trees. The planting schedule of the project provides insight into whether the project aims to fell the trees and replant them throughout the project lifetime (rotational forestry), or if it’s planting them for the long term (conservation forestry).
Projects whose planting schedules are taking place today or in the future also open up the possibility for buyers of credits to visit the project as the planting is happening. This can be for marketing purposes, or to conduct an additional check on the project progress.
In order to understand afforestation projects’ planting schedules, we looped through the project documents with the following query:
What is the planting schedule for the project?
Users can also specify how the response should be generated:
Export the data in two data points: start date and end date.
The table below shows the response from AIDER. The tool was accurately able to pick out the key data points; however, the response needs some minor tweaking to be incorporated cleanly into a wider dataset. This is something that users can attempt to do by tweaking the prompt, or using an external program.
For more information about AIDER, please get in touch.