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Users fill out a profile to state their location, age, gender, and music preferences. They can also select similar demographics of those they would like to add to their tribe to enable tailored recommendations and users to feel safe and comfortable.


Matching users manually was time-consuming, so the VEC’s Digital Project Engineers developed and demonstrated a range of AI algorithms to solve this problem. They utilised popular event sites like Skiddle to extract venues, music genres, and other relevant information to find even more options and available events in real-time.


Implementing such technologies to the GigMate systems will reduce the time spent on data inputting for unveiling matches.

The systems can also automate communications to the site users, highlighting new events in real-time so the quality of the service can be improved, leading to enhanced customer service and satisfaction levels.

GigMate is exploring how they can expand this technology to extend event searches to include sporting and student society matching, improving social groupings, and alleviating loneliness within an even wider demographic.

For more information on GigMate, please click here.

Click here for the downloadable case study.