The challenge
Nexteria was collecting feedback after workshops and discussions manually. But the real problem was that volunteers still had to process the raw data.
Manual evaluation also created inconsistency. Some events got processed, some did not, and nobody wanted to spend hours reading every open-text response just to pull out the same recurring themes again.
How we helped
We built a pipeline that, once the event is over, gathers the raw data and filters out irrelevant noise before a human ever has to touch it.
Using AI, each event gets a synthesis that turns hundreds of responses into a short professional summary with themes, representative quotes, and recommendations.
The output is a set of finished documents, ready to be sent to guests and lecturers as a thank-you.
Results
Hours of manual response review were replaced by consistent reporting after every event.
Guests and lecturers receive a more professional and consistent follow-up after every event.
A short AI summary with themes, representative quotes, recommendations, and what to keep or improve next time.
A clean document with relevant feedback organized by question, respondent count, and NPS context.
Recurring themes, strong quotes, and room for improvement become visible much faster.
Estimated impact
30 - 60 min
We reduced the original processing time for one event to under 30 seconds.
30+ hrs / month
Estimated time returned to the Nexteria team with repeated weekly use.
100%
Zero manual steps between feedback submission and the final report after the deadline, with no human intervention.