Croissant

Croissant helps public sector organisations work smarter and faster, freeing up resources to deliver for the public.

Traditional methods of analysing large bodies of written information are extremely time-consuming. The Ministry for Environment estimates that Croissant reduces the time needed to manually tag submissions by up to 90 percent.

Plus, security measures built into Croissant help protect the submitter's personal information.

Croissant automatically (or manually) tags each submission with keywords that relate to its content. From there, submissions are sorted and analysed. Tags also identify submissions made from specific groups (such as companies, iwi, or regions) to ensure they are addressed appropriately.

There are three different modes that Croissant works in: manual, unsupervised, and supervised. 

The manual mode allows users to upload a taxonomy and manually tag sections of written text that align with categories within that taxonomy (for example, submissions that support the proposal versus those that do not). Croissant acts as an enormous set of digital highlighters, assigning a different ‘colour’ to each tag to visually represent the results. It then records and counts the number of submissions under each tag.

In its unsupervised mode, the machine learning module identifies groups of submissions that contain similar ideas. This mode provides an overview of a large body of text and creates an interactive map of all submissions, grouping similar ones together, all without human intervention. The results can then be used to help develop a tagging taxonomy appropriate across all submissions.

In its supervised mode, the module is taught to associate manually applied tags with specific text under review. It then automatically applies those same tags to the remaining untagged text.

Croissant shows the status of all of your consultations, the submission themselves, and how much of the text has been tagged.