---
title: Using AI to Contextualize VCM Projects
description: AlliedOffsets recently launched an AI Document Reader (AIDER) tool, which allows users to extract data out of project documents in a structured way.
image: https://blog.alliedoffsets.com/hubfs/Household%20Devices.png
---

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# Using AI to Contextualize VCM Projects

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- Using AI to Contextualize VCM Projects

[Anton Root](https://blog.alliedoffsets.com/author/anton-root) 05/06/2024 [AlliedOffsets Data Updates](https://blog.alliedoffsets.com/tag/alliedoffsets-data-updates)

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 1 Minutes

AlliedOffsets recently launched an AI Document Reader (AIDER) tool, which allows users to extract data out of project documents in a structured way.

The tool can be employed to extract information from VCM documents, enabling users to:

- Conduct bespoke analysis across project sectors or geographies
- Extract niche data about projects that’s not found easily in the registry
- Provide context around project activity

 

In this blog, we showcase an example of how AIDER is used to put projects into a wider context.

![Household Devices](https://blog.alliedoffsets.com/hs-fs/hubfs/Household%20Devices.png?width=239&height=220&name=Household%20Devices.png)

## Household Devices: An Exploration

Household devices (typically, clean cookstoves or water purifiers) generate carbon dioxide emissions reductions by displacing traditional cooking or purification methods with those that need less biomass fuel. Stated simply, these projects enable people to collect or cut down less firewood, leading to fewer trees being cut.

Each project, however, is different in what activity it’s displacing. And the household devices that the projects employ operate in different ways. This information is important for obtaining a clear understanding of the project and how it generates credits.

Project descriptions do not provide enough information to surface this type of information; the only option has been to comb through hundreds of pages of documentation.

The AIDER tool, however, allows users to contextualize dozens of projects in seconds. Our previous blog explained how the tool works; in this blog, we showcase the results that are generated using the document reader.

## Results

In order to better understand how household devices are generating credits, we use the following query:

`What devices are being used by households today? How is this device going to reduce emissions? `

Users can also specify how the response should be generated, stylistically: 

`Extract the data in a succinct way.`

The table below shows the response. For each project, the response records the project ID, country, registry, sector, document name, the prompt, and the response. 

The responses allow users to quickly understand what the current activity is, and how the project helps to lower emissions. 

 

For more information about AIDER and to sign up for an account! 

[Please get in touch](https://alliedoffsets.com/contact/)

 

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#### [AlliedOffsets Launches AI Document Reader Previous Post](https://blog.alliedoffsets.com/alliedoffsets-launches-ai-document-reader)

#### [Three Companies Own 45% of All DAC Patents: A CDR Patent Analysis Next Post](https://blog.alliedoffsets.com/three-companies-own-45-of-all-dac-patents-a-cdr-patent-analysis)

### Leave a Reply

---

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