VoteScope AI: Voter Turnout Intelligence for SPOs & DReps

[Proposal setup] Proposal title

Please provide your proposal title

VoteScope AI: Voter Turnout Intelligence for SPOs & DReps

[Proposal Summary] Budget Information

Enter the amount of funding you are requesting in ADA

99975

[Proposal Summary] Time

Please specify how many months you expect your project to last

8

[Proposal Summary] Translation Information

Please indicate if your proposal has been auto-translated

No

Original Language

en

[Proposal Summary] Problem Statement

What is the problem you want to solve?

Low turnout and idle SPO/DRep delegations leave large portions of Catalyst voting power unused, weakening governance legitimacy and decision quality.

[Proposal Summary] Supporting Documentation

Supporting links

• https://github.com/fuguswarm/votescope_AI_demo
,
• https://t.me/DeveloperEcosystem
,
• https://github.com/Sapient-Predictive-Analytics/dataportal/tree/main
,
• https://github.com/Sapient-Predictive-Analytics/dataportal/blob/main/community/community.md

[Proposal Summary] Project Dependencies

Does your project have any dependencies on other organizations, technical or otherwise?

No

Describe any dependencies or write 'No dependencies'

No dependencies

[Proposal Summary] Project Open Source

Will your project's outputs be fully open source?

Yes

License and Additional Information

Code will be fully open source (MIT License). Non-software material ranging from datasets to videos will be under a Create Commons license.

[Theme Selection] Theme

Please choose the most relevant theme and tag related to the outcomes of your proposal.

DAO

[Campaign Category] Category Questions

Describe what makes your idea innovative compared to what has been previously funded (whether by you or others).

VoteScope AI is innovative because it combines real-time data ingestion, AI clustering, and gamified incentives to activate idle Catalyst voting power. Unlike traditional monitoring tools, it focuses on privacy-preserving turnout intelligence and soft reputation rewards, turning unused delegations into active governance participants without coercion.

Describe what your prototype or MVP will demonstrate, and where it can be accessed.

The MVP will demonstrate a live dashboard with turnout heatmaps, delegation activity profiles, and early leaderboards for SPOs and DReps. It will show how AI clustering detects participation patterns, how alerts flag inactive voting power, and how gamified recognition, including badges and rankings, can encourage delegations to take action while ensuring full voter anonymity.

Describe realistic measures of success, ideally with on-chain metrics.

Success will be measured on-chain through higher turnout among monitored delegations, active leaderboard updates, and regular refresh of voting data. Targets include 15+ engagement signal listings in year one, onboarding 10 SPOs and 5 DReps, with at least half appearing in leaderboards each round.

[Your Project and Solution] Solution

Please describe your proposed solution and how it addresses the problem

VoteScope AI is an AI-powered governance analytics tool designed to activate idle voting power by tracking voter turnout, mapping engagement trends, and incentivizing participation through soft, reputational rewards.

How it Works:

• Ingest real-time Catalyst voting data and normalize it for analysis.

• Use AI clustering to profile delegations by turnout patterns.

• Apply sentiment analysis to detect disengagement signals from public channels.

• Display turnout heatmaps and distribution visualizations for SPOs/DReps.

• Issue public, non-targeted nudges when large delegations remain inactive.

• Reward active participation through leaderboards, badges, and governance participation scores.

Voter Incentive Framework:

• Leaderboards – Publicly rank active SPOs/DReps during each voting period.

• Recognition Badges – Earnable visual marks for consistently high turnout.

• Participation Scores – Long-term metric reflecting governance engagement.

• Public Acknowledgments – Post-vote highlights of top-performing delegations.

Privacy-First:

• All analytics are aggregated and anonymized — no personal voter targeting.

API Risk Mitigation:

• VoteScope AI will connect to Catalyst’s official data feeds where available. If direct API access is restricted or unavailable, the platform will use alternative methods such as public datasets, mirrored repositories, and secure data extraction scripts to ensure uninterrupted operation. This flexibility ensures timely delivery regardless of changes to Catalyst’s data infrastructure.

Complement to "DRep AI Assistant Proposal"

VoteScope AI acts as the eyes while the DRep AI Assistant acts as the voice. VoteScope surfaces turnout patterns and activation opportunities; the DRep AI Assistant uses that intelligence to craft persuasive, timely outreach.

[Your Project and Solution] Impact

Please define the positive impact your project will have on the wider Cardano community

VoteScope AI addresses one of the most persistent governance challenges in Catalyst: the underutilization of voting power. By activating idle delegations and incentivizing participation, the platform directly strengthens Catalyst’s legitimacy, decentralization, and decision-making quality.

Short-Term Impact

• Immediate Turnout Increase: SPOs and DReps will have access to real-time turnout analytics, allowing them to take timely action to mobilize delegations during the voting period.

• Enhanced Voter Awareness: Delegators will see that participation is both recognized and valued, encouraging them to take part in the governance process.

• Complement to DRep AI Assistant: With VoteScope surfacing turnout data and DRep AI Assistant delivering tailored governance education, the result is a more informed and responsive voting body.

Mid-Term Impact

• Performance Tracking: SPOs and DReps can track their delegation’s participation trends over multiple rounds, enabling strategic improvements in engagement.

• Positive Peer Pressure: Leaderboards and badges will create a healthy competitive environment where SPOs/DReps are motivated to maintain top participation rankings.

• Knowledge Sharing: High-performing delegations can share best practices, creating a knowledge loop that benefits the broader Catalyst ecosystem.

Long-Term Impact

• Sustained Culture of Engagement: Repeated reinforcement of participation norms leads to long-lasting behavior change — voting becomes the expectation, not the exception.

• Cross-Platform Governance Influence: VoteScope AI’s anonymized turnout insights could be adapted for other governance models, positioning Catalyst as a pioneer in turnout activation technology.

• Institutional Memory: By recording historical turnout patterns, the platform builds a valuable dataset for researchers, policymakers, and future governance improvements.

Ecosystem Benefits by User Group

• SPOs: Gain visibility into delegation activity, strengthen community bonds, and enhance their reputation through consistent governance engagement.

• DReps: Access actionable intelligence to focus outreach efforts where they matter most.

• Delegators/Voters: Receive recognition for engagement, see the direct impact of their participation, and feel more connected to decision-making.

• Catalyst Admins & Governance Researchers: Access anonymized participation data for monitoring governance health and identifying systemic risks.

KPIs:

• +15% voter turnout among monitored delegations in the first Catalyst round of use.

• At least 10 SPOs and 5 DReps onboarded within 3 months.

• 50% of onboarded SPOs/DReps appear on the leaderboard at least once per round.

• API endpoints are actively available for integration, with early adoption by external governance tools within the first 3 months.

• 25% adoption rate for recognition badges among top-performing delegations.

While our KPIs provide clear, quantifiable targets, the real value of VoteScope AI will also be assessed through qualitative and ecosystem-level observations:

• User Feedback Loops – Gathering feedback from SPOs, DReps, and voters through post-round surveys and interviews to understand usability, motivation, and perceived influence on turnout.

• Ecosystem Awareness – Monitoring Catalyst governance forums, Discord, and Telegram groups for mentions, recommendations, or critiques of VoteScope AI.

• Behavior Change Tracking – Observing shifts in participation levels before and after tool introduction to detect whether dormant voting power is being activated.

• Governance Tool Integration – Tracking how often VoteScope AI’s outputs are linked, cited, or embedded in external dashboards or governance communication channels.

• Retention Across Rounds – Measuring whether SPOs and DReps continue using VoteScope AI in subsequent funding rounds, indicating lasting value rather than one-time novelty.

This combined quantitative (KPIs) and qualitative (impact measures) approach ensures that VoteScope AI is not only delivering features, but also creating a tangible, sustained improvement in voter participation and governance engagement.

In sum, VoteScope AI provides measurable, repeatable, and scalable improvements in voter engagement that strengthen Catalyst governance for years to come.

[Your Project and Solution] Capabilities & Feasibility

What is your capability to deliver your project with high levels of trust and accountability? How do you intend to validate if your approach is feasible?

Our team has consistently delivered funded governance tools in Catalyst with transparency and accountability. With proven expertise in data, AI, and governance, we are equipped to execute VoteScope AI with the same reliability and professionalism.

Team Expertise

• Data Engineering & Blockchain Analytics: Delivered production-grade data ingestion pipelines for on-chain governance metrics.

• AI Development: Experience building clustering, sentiment analysis, and anomaly detection models tailored to governance data.

• Frontend & UX Design: Skilled in creating intuitive, responsive dashboards that cater to both technical and non-technical users.

• Governance Process Knowledge: Deep understanding of Catalyst’s voting cycles, DRep operations, and SPO-delegator dynamics.

Technical Approach

• Data Ingestion Layer: Designed to pull from Catalyst APIs when available; alternative sources include mirrored datasets, public repositories, and secure extraction scripts for resilience.

• Analytics Core: AI-driven clustering to group delegations by engagement patterns, combined with sentiment and trend detection for timely insights.

• Visualization & Incentives Layer: Real-time heatmaps, interactive dashboards, leaderboards, badges, and participation scores, all mobile-optimized for accessibility.

Prototype turnout heatmap visualizing voter participation patterns across delegations.

• Privacy Compliance: Aggregated, anonymized outputs to ensure no personal voter information is exposed.

Delivery Track Record

• Successfully completed multiple Catalyst-funded governance tools with verifiable public repositories and close-out reports.

• Delivered on both technical build and community engagement aspects, including integrating user feedback into iterative releases.

https://github.com/Sapient-Predictive-Analytics/dataportal/blob/main/community/community.md

• Maintained transparency with regular progress updates and milestone demos, reinforcing trust with funders.

Risk Management

• API Access Risk: Mitigated through multiple data ingestion pathways, ensuring platform resilience if Catalyst API access changes.

• Adoption Risk: Addressed via gamification (leaderboards, badges) and social proof to encourage ongoing use by SPOs and DReps.

• Technical Risk: Reduced by leveraging proven frameworks and modular architecture, allowing incremental releases rather than a single big launch.

Why We Can Deliver

• The VoteScope AI project scope is clear, phased, and technically realistic given our resources.

• We have the in-house skills to build, test, and deploy the full stack without reliance on unproven external teams.

• The system is designed to be self-sustaining post-launch, with minimal maintenance costs and no dependency on continuous Catalyst funding.

In addition to this proposal, our team has contributed open-source governance tooling to the Catalyst community, such as the dataportal repository used by SPOs, DReps, and community researchers. These prior projects are not part of VoteScope AI, but they showcase our capacity to deliver transparent, production-grade tools that support ecosystem needs

https://github.com/Sapient-Predictive-Analytics/dataportal/tree/main

We don’t just have the skills to build this. We have already earned the community’s trust by delivering on every funded commitment. VoteScope AI is the next step in that journey.

[Milestones] Project Milestones

Milestone Title

Backend Data Ingestion

Milestone Outputs

1. Build a backend pipeline to continuously ingest Catalyst voting data.
2. Normalize raw inputs into a consistent, query-ready format.
3. Implement secure, performance-optimized database storage.
4. Set up automated refresh scheduling to update records within

Acceptance Criteria

1. Pipeline connects successfully to at least one Catalyst data source.
2. Updates occur within 30 seconds of new data availability.
3. System handles a minimum of 1,000 records without error.
4. Data is stored in a secure and query-optimized structure.

Evidence of Completion

1. GitHub repository with backend code.
2. Public sample dataset demonstrating normalized format.
3. Demo video showing ingestion and refresh scheduling.
4. Architecture documentation describing data flows and storage.

Delivery Month

2

Cost

19950

Progress

20 %

Milestone Title

AI Clustering & Participation Pattern Analysis

Milestone Outputs

1. Develop an AI clustering model to profile delegation engagement behaviors.
2. Group SPOs and DReps into at least three categories (e.g., consistent, sporadic, dormant).
3. Train the model on anonymized historical Catalyst voting data to ensure privacy.
4. Generate exportable cluster profiles that can be reused for governance analysis.

Acceptance Criteria

1. Clustering output demonstrates clear and distinct engagement types.
2. Model achieves verified accuracy against a defined test dataset.
3. All inputs remain anonymized with no personal voter data exposed.
4. Methodology is documented and reproducible by reviewers.

Evidence of Completion

1. Public GitHub repository containing model code.
2. Exported datasets showing cluster results.
3. Model evaluation report validating accuracy.
4. Methodology document available for reviewer inspection.

Delivery Month

4

Cost

19950

Progress

40 %

Milestone Title

Turnout Heatmaps & Distribution Visualizer

Milestone Outputs

1. Develop interactive turnout heatmaps to highlight participation patterns across SPOs and DReps.
2. Implement distribution charts for voting power by delegation and challenge category.
3. Enable filtering by SPO, DRep, and challenge, returning results within seconds.
4. Ensure dashboard compatibility across desktop and mobile for accessibility.

Acceptance Criteria

1. Heatmaps display live or near-real-time data streams.
2. Filters return correct results within two seconds.
3. Dashboard works across modern browsers and mobile devices.
4. Visualizations match stored data with no discrepancies.

Evidence of Completion

1. Public dashboard link showing heatmaps and charts.
2. Screenshots demonstrating interactive filters.
3. Code repository containing visualizer implementation.
4. User testing summary confirming usability and accuracy.

Delivery Month

5

Cost

19950

Progress

60 %

Milestone Title

Public Alert System for Inactive Voting Power

Milestone Outputs

1. Implement automated alerts for large inactive delegations.
2. Display anonymized inactivity messages on the public dashboard.
3. Integrate alert system with turnout visualizer for contextual visibility.
4. Provide configurable thresholds to adjust sensitivity of alerts.

Acceptance Criteria

1. Alerts trigger correctly at pre-configured inactivity levels.
2. Messages never reveal individual voter identities.
3. Alert logs correspond accurately with system events.
4. Alerts appear clearly on the public dashboard.

Evidence of Completion

1. Configuration file in repo showing alert thresholds.
2. Screenshots of alerts in live dashboard context.
3. Demo video of integration with turnout visualizer.
4. Log export verifying alert triggers.

Delivery Month

6

Cost

14900

Progress

70 %

Milestone Title

Community Incentives & Leaderboard Integration

Milestone Outputs

1. Create a public leaderboard ranking active SPOs and DReps based on participation.
2. Implement a recognition system highlighting consistent governance engagement.
3. Automate score calculations and updates during voting periods.
4. Deliver real-time visibility of rankings and reputational signals.

Acceptance Criteria

1. Leaderboard updates occur within one minute of new data.
2. Recognition signals are assigned automatically to eligible delegations.
3. Rankings match underlying participation data with no discrepancies.
4. Incentive system functions without manual intervention.

Evidence of Completion

1. Leaderboard updates occur within one minute of new data.
2. Recognition signals are assigned automatically to eligible delegations.
3. Rankings match underlying participation data with no discrepancies.
4. Incentive system functions without manual intervention.

Delivery Month

7

Cost

14900

Progress

80 %

Milestone Title

Final Close-Out Report & Video Submission

Milestone Outputs

1. Compile a final project close-out report summarizing all deliverables, KPIs, and outcomes.
2. Produce a 5 minute close-out video presenting purpose, process, and results.
3. Document lessons learned and recommendations for future governance tools.
4. Consolidate all project assets into a single public repository for community access.

Acceptance Criteria

1. Close-out report covers all milestones, KPIs, and lessons learned.
2. Close-out video clearly communicates project scope and results.
3. All deliverables are available via permanent public links.
4. Repository includes code, documentation, and project assets in one place.

Evidence of Completion

1. Public PDF close-out report hosted online.
2. Close-out Video link published on an accessible platform.
3. Final GitHub repository containing project assets.
4. Close-out post published in Catalyst forum.

Delivery Month

8

Cost

10325

Progress

100 %

[Final Pitch] Budget & Costs

Please provide a cost breakdown of the proposed work and resources

We use 2 standardized hourly rates:

Development: 100 ADA/hour

Office & Project Management: 75 ADA/hour

Milestone Allocation

Milestone 1: Backend for Real-Time Data Ingestion

183 dev hrs + 22 PM hrs = 19,950 ADA

Deliverables: Backend pipeline for Catalyst voting data ingestion, normalization, secure storage, and automated refresh.

Milestone 2: AI Clustering & Participation Pattern Analysis

183 dev hrs + 22 PM hrs = 19,950 ADA

Deliverables: Clustering model grouping SPOs/DReps into engagement categories, trained on anonymized historical data.

Milestone 3: Turnout Heatmaps & Distribution Visualizer

183 dev hrs + 22 PM hrs = 19,950 ADA

Deliverables: Interactive turnout heatmaps and charts with filters for SPOs, DReps, and challenges.

Milestone 4: Public Alert System for Inactive Voting Power

137 dev hrs + 16 PM hrs = 14,900 ADA

Deliverables: Alert triggers for large inactive delegations, anonymized messages, dashboard integration.

Milestone 5: Community Incentive & Leaderboard Integration

137 dev hrs + 16 PM hrs = 14,900 ADA

Deliverables: Public leaderboards, badges, real-time scoring system for active SPOs and DReps.

Milestone 6: Close-Out Report & Video Submission

95 dev hrs + 11 PM hrs = 10,325 ADA

Deliverables: Final close-out report, close-out video presentation, GitHub repository with all code and documentation.Total = 99,975 ADA (within the 100,000 ADA cap).

In VoteScope AI, costs for project management, documentation, reporting, and community engagement with SPOs and DReps are already covered in our PM allocation, ensuring accountability and visibility without requiring a separate marketing budget.

[Final Pitch] Value for Money

How does the cost of the project represent value for the Cardano ecosystem?

The value for money in this proposal comes from giving the Cardano ecosystem practical, data-driven insight into how the community behaves. As we move into the Voltaire era, voting power will become more decentralized. That’s healthy, but it also makes it even more important to understand how social influence, participation trends, and dominant voices shape decisions. Without this visibility, governance risks being skewed by a small but vocal group.

Our budget is focused on what really matters: mapping community behavior, building accessible dashboards, and publishing reports that highlight where influence is concentrated and where silent contributors can be amplified. We’ve kept costs lean and transparent. Development work is budgeted at 100 ADA/hour and project management at 75 ADA/hour, which is in line with freelance and professional rates in Singapore and similar markets. This way, every ADA requested is tied directly to delivery rather than overhead.

What the project brings back to the ecosystem is clear:

• Efficient use of funds by limiting spend to the essentials that make this tool useful from day one.
• Scalability so the framework can extend beyond Catalyst, supporting DAOs and governance experiments across Cardano.
• Community impact by making participation fairer, surfacing neglected voices, and helping contributors and DReps make informed choices.
• Proven expertise from a multidisciplinary team experienced in trading, risk management, analytics, governance, and software delivery.
• Return on investment through stronger participation, better legitimacy in funding outcomes, and higher trust as Catalyst transitions into Voltaire.

Our team has already completed funded proposals in Fund 7, Fund 8, and Fund 11. That track record shows not only our ability to deliver but also our respect for the Cardano community and the funds entrusted to us.

[Required Acknowledgements] Consent & Confirmation

Terms and Conditions:

Yes