The vendor required to provide election night reporting (ENR) system that provides accurate, timely, and secure election results to the public and stakeholders.
- Gather vendor capabilities and approaches for an ENR system that ensures transparency, security, and scalability.
- Statewide election night results reporting for all contests and precincts
• Manual processes
• No document customization
• No full system control to create standardized work flows across county users
• No just-in-time training
• No full access to regression testing during enhancements
• No full reporting capabilities
• No scalability
- General needs
1. Identified critical capabilities for this type of solution:
• Cots (commercial off the shelf) ENR for statewide election night reporting.
• SaaS solution
• Ability for all fifteen (15) counties to upload their results on election nights.
• Ability to work with multiple county level EMS and ENR solutions.
• Presidential, congressional, legislative, and statewide races are implemented.
• Must be able to report by congressional, legislative, as well as statewide districts.
• Name translation – the system allows an election user to map contest names between what the state called a contest and what the jurisdiction called a contest.
• Election night support:
o Needs to support the night after election night up to eleven (11) days after elections.
o Needs to have an auto-publishing function for all counties or minimally a granularity of auto-publishing for each of the individual counties.
o Display voter turnout.
• Multiple language support. (English and Spanish)
2. Other capabilities
• Precinct reporting.
• Election management system to include candidate and lobbyist portal integrations.
• Display write-in votes and possibly the candidate photo.
• A ballot progress page
o Counties enter approximate number of outstanding ballots (in up to 4 various categories) and with each upload, the numbers are calculated and populates a page section of the website with results.
3. Artificial intelligence capabilities
• AI utilization and capabilities
o Any AI technologies or methodologies integrated into your solution.
o Identify specific use cases (e.g., data validation, fraud detection, intelligent search, predictive analytics).
o Indicate whether AI is used in real-time decision-making or as a support tool.
• Security and data protection
o Explain how AI components interact with sensitive voter data, including personally identifiable information (PII) and protected addresses.
o Security measures in place to prevent unauthorized access, data leakage, and model exploitation.
• Compliance, ethics, and transparency
o AI solution adheres to federal and state regulations governing data use and automated decision-making.
o Mechanisms for ensuring explain ability of AI outputs to system users and administrators.
o Outline strategies for bias detection and mitigation, especially in areas affecting eligibility or access.
• Performance and monitoring
o Metrics for AI components, including:
1. Accuracy
2. Response time
3. Scalability
4. AI performance is monitored, validated, and updated over time.
• Integration and interoperability
o Any dependencies or third-party services used in delivering AI functionality.
