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Win at least 50% time back during the analysis and reporting phase
Report and close the feedback loop more often and better
Are you drowning in responses to open-ended questions and cluttered spreadsheets? Struggling to come to clear conclusions?
Let Go Vocal's AI analytics tool do the resource-intensive data analysis for you, so you can focus on what really matters - advising on decision and policy-making and connecting with residents.
The analysis phase just got fun with Go Vocal
Organize community input using advanced tagging possibilities.
Analyze and instantly summarize big data sets automatically
Transparent input sourcing for human checks and accurate summaries.
Spot patterns across groups and uncover statistically significant links between demographics, lived experience, and priorities.
Our AI assistant speaks government language, guaranteeing you get relevant insights from your data.
Create impactful reports reusing the (editable) AI-generated summaries.
Thanks to the AI assistant, we saved about 10 hours, or 50%, in the analysis phase. These AI-generated summaries were a good base to develop the reports needed to share with the public and stakeholders, enhancing transparency and inclusivity in decision-making processes.
Esther Pickard
Digital and Web Product Manager, Cambridge City Council (UK)
In this guide, we'll explore the potential of AI as a way for local governments to amplify the voice of your residents, particularly zooming in on its benefits and use cases for community engagement.
Engaging 60,000+ community members: Toronto Centre scaled participatory budgeting across 14 neighborhoods
When Toronto Centre embarked on its participatory budgeting initiative, it faced a fundamental challenge that many government agencies encounter: how do you meaningfully engage diverse communities in complex decision-making while maintaining administrative efficiency? The solution – a structured, technology-supported approach using Go Vocal – has now successfully allocated over CA$2.25 million across 14 neighborhoods over multiple cycles, creating a replicable model for large-scale community engagement.