Reduction Recommendations

Last updated 19 days ago

The Reduction Recommendations screen allows you to view, evaluate, and manage AI-generated emission reduction suggestions based on your organization’s previous-year emission data. This module helps you understand reduction potential across all sub-category levels.

Access this page via: Reduction Plans → Recommendations

Reviewing AI-Generated Recommendations

The system automatically lists relevant reduction recommendations for the selected scope and sub-category.

If no recommendations have been generated before, click “Get new suggestions” to allow the AI to create a new set of recommendations.

Each recommendation card includes the following information:

  • Recommendation Title

  • AI Suggested label

  • Impact Level: High / Medium / Low

  • Scope and Sub-category Information

  • Estimated Annual Emission Reduction (tCO₂e/year)

  • Recommendation Type: Operational, Behavioral

  • Difficulty Level: High, Medium, Low

  • Relevant Facility (or Facilities)

Each card also includes two explanatory sections:

Why it matters: Explains why this recommendation is important and which emission issue it addresses.

How to take action: Provides actionable steps for implementing the recommendation. At the bottom of each card, you can indicate whether the recommendation was helpful.

Category & Facility Selection

At the top of the page, you can navigate between:

  • Scope 1

  • Scope 2

  • Scope 3

Each scope displays its related sub-categories.

Using the Facility filter on the right, you can limit the recommendations to specific facilities.

Requesting Alternative Recommendations

If a recommendation is not suitable, click “Suggest alternative” to generate an AI-created alternative suggestion for the same category.

Actions on Recommendations

Each recommendation card includes an Actions menu with the following options:

  1. Dismiss: Marks the recommendation as not relevant or not applicable to the organization.


(Does not delete it; only updates its status.)

  1. Mark as Done: Indicates that this recommendation has already been implemented within the organization. This helps improve future AI recommendation outputs.

Adding Recommendations to Favorites

If you want to review a recommendation later or mark it as important, click the bookmark icon on the card.

Favorited recommendations are stored under the Bookmark page.

Favorites Page

The Favorites screen displays only the recommendations that you have saved.

Available actions:

  • Search bar: Search by recommendation title

  • Filters: Narrow results by:

    • Scope 1 / Scope 2 / Scope 3

    • Sub-categories

    • Recommendation Type (Operational, Behavioral, etc.)

    • Difficulty Level

    • Facilities

    • Favorite Status

Each recommendation card in this section also includes Actions → Dismiss / Mark as Done, just like the main recommendations view.