Tender Matching and Labelling AI Module

Purpose:  

To match suppliers with tenders that best fit their capabilities and criteria, optimizing their participation.

Process:

Data Input: The module takes detailed tender documents and supplier profiles as inputs.

Criteria Extraction: Key aspects such as price, type of service or good, and other relevant factors are extracted from the tenders using NLP techniques.

Numeric Labelling: These aspects are translated into a framework with numeric labels, representing various attributes such as:

Price Range:   Numeric value indicating the budget category.

Service Type:   Numeric code corresponding to the type of service or product required.

Complexity Level:   Numeric rating of the project's complexity or technical requirements.

Geographical Location:   Numeric code representing the location of the project.

Supplier Profile Matching:   Suppliers provide their criteria, such as the services they offer, price range, and geographical preferences. These criteria are also converted into numeric labels.

Matching Algorithm:   The module uses a matching algorithm to compare the numeric labels of tenders and suppliers. This algorithm calculates the degree of match based on the provided criteria.

Recommendation Display:   The module displays a list of tenders that best match the suppliers' criteria, ranking them based on the degree of match. Suppliers can then view and decide on which tenders to pursue.