It was inspired by use of AI in engaging of public feedback which usually a slow manual process . by the lack of digital data in Feedback management.
What it does
Define campaigns of public feedback . uses AI to review the comments and classify them as positive and negative.gathers public feedback on planning. accuracy - the percentage of predictions that are correct. It should be about 85-90%.
How we built it
With Stepzen's GraphQL Studio for Api development, was used to design API for feedback plan. Used Vue to build the frontend. and the web based feedback plan .and the GraphQL API for feedback analysis . we use sentiment API and review to analyze the sentiment. Trained IMDB dataset for online sentiment analysis.
Challenges we ran into
One of the challenges is displaying feedback plan to Vue app . transforming response data to sentiments display as rows . Was complicated Getting the positive, negative sentiment from API on submitted reviews.
Accomplishments that we're proud of
developed Case feedback management app that impacts public engagement. With StepZen's easy to use GraphQL CLI.
What we learned
Conclusion We can include AI along side the public sentiment to initiate change. How to setup feedback using GraphQL Api and the impact of reviews on planning,I learned you can classify reviews using AI.its the feedback engagement that impacts how the outreach is extended.
What's next for AI Engage
more sustainable feedback
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