The document outlines a federal government Request for Proposal (RFP) for an AI-powered knowledge management and decision support system. The primary goal is to optimize the Tri-Command Critical Path process by automating workflows, integrating a cross-domain long-range calendar across NIPR, SIPR, and CENTRIX-K enclaves, and auto-generating the COM Calendar Sync. The system must also include a bilingual transcription service for Korean and English with speaker attribution, searchable archives, and automated extraction of actionable items. A centralized knowledge management portal will provide a unified interface for all tools. The implementation strategy involves four phases, focusing on transcription, workflow automation, calendar integration, and calendar sync automation, with comprehensive testing and training. Success will be measured by workflow automation, unified calendar management, elimination of manual data manipulation, and streamlined transcription and meeting analysis. Key contract considerations include phased delivery, a two-year warranty, five-year maintenance, and government retention of unlimited software rights and data ownership.
The Tri-Command requires critical path operational support across three key areas to enhance efficiency and decision-making. First, speaker diarization is needed to automate transcription of General Officer/Flag Officer meetings, addressing challenges with manual note-taking, improving accuracy, and ensuring clear context for staff actions. Second, a cross-domain automation solution is sought to facilitate secure, real-time data synchronization across NIPRnet, SIPRnet, and CENTRIX-K enclaves, specifically to automate master calendar updates and eliminate manual data entry errors. Third, dedicated expertise is required for the Commander's decision-making cycle, encompassing nomination, vetting, tracking, and delivery of critical information, alongside assessing outcomes to demonstrate return on investment to leadership. This initiative aims to streamline processes, mitigate data errors, and provide clear insights for strategic decision-making within the Tri-Command.