The Vendor is required to provide for a comprehensive Cloud-Based Unified Communications (UCaaS) platform.
- Solution must provide a seamless replacement for the District’s legacy telephony infrastructure while delivering an integrated suite of voice, safety, and messaging applications.
- The District requires a future-ready system that prioritizes emergency communication, high-availability cloud architecture, and robust integration with existing campus security and paging assets.
- This transition is a core component of the District’s commitment to providing a safe, innovative, and healthy learning environment for our approximately 4,000 students and 480+ staff members.
- Objective of this project is to implement a unified platform that eliminates on-premise PBX hardware while delivering enterprise-grade voice, emergency notification, and messaging capabilities.
- Responsible for the seamless migration of 870 extensions and 20 e-fax lines across 12 distinct school sites.
- Key project drivers include the enhancement of school-wide safety protocols, integration with existing legacy security and paging assets, and the provision of a modernized user experience across all DSD platforms, including ChromeOS, macOS, and mobile devices.
- Project Goals:
• Unified cloud architecture: establish a centralized, high-availability system with zero on-premise server requirements.
• Enhanced safety & compliance: deploy a granular e911 system that tracks locations down to the physical switch port to comply with act and provides "silent monitoring" security features.
• Interoperability: guarantee seamless connectivity between the new cloud platform and existing analog Valcom and carhawk public address systems.
• Value-added recovery (optional): the district welcomes proposals for hardware buy-back or trade-in credits for our 825 retired Mitel/Shoretel handsets to offset initial implementation costs.
• Implementation: complete a comprehensive district-wide rollout during the summer 2026 window, supported by a hybrid training model.
- User interface:
• Intuitive design: the system must offer a user-friendly interface that requires minimal training for basic operations across all platforms (ChromeOS, mac, windows, and mobile).
• On-device instructions: handsets should display native, context-sensitive help or instructional prompts directly on the screen to guide users through common tasks.
• Customization: administrators and teachers must have the ability to customize dashboard layouts, speed-dial labels, and notification preferences.
• Accessibility: all software interfaces must adhere to WCAG 2.1 level AA standards to ensure compatibility for users with disabilities.
- Call management and control:
• Automated handling: provisioning for sophisticated auto-attendants and hunt groups with the ability to set different schedules for school hours, after-hours, and holidays.
• Call security: native ability for users to block incoming numbers and for administrators to manage a global "block call list" to mitigate spam and harassment.
• Recording and monitoring: support for "push-button" call recording for classrooms and administrative offices, with secure cloud storage and easy retrieval via the GUI.
• Communication tools: capability to broadcast information or send text-based notifications to students' or staff devices in real-time
- Reporting and analytics:
• Data visualization: clear presentation of call logs, usage patterns, and system health through integrated graphs and charts.
• Customizable reports: ability to generate and schedule automated reports based on specific extensions, departments, or school sites.
• Trend analysis: built-in tools for analyzing student or staff engagement and identifying unusual call volume patterns.
- Artificial intelligence (AI) transparency and governance:
• Operational purpose: define the specific utility of each AI feature (e.g., administrative automation vs. Security analysis).
• Data sources: disclose what data the AI pulls from (e.g., call metadata, voice patterns, or directory info) and whether it utilizes district data to "train" global models.
• Training provenance: provide information on the original datasets used to train the AI and steps taken to mitigate algorithmic bias.
• Human-in-the-loop: describe the mechanisms for human oversight and the ability for district admins to opt out of specific AI functionalities.
