Development of an AI-Driven Knowledge Management Platform for Dynamic Team Collaboration

The organization faces difficulties in managing and structuring multimedia knowledge content, including videos and recordings, resulting in inefficient information retrieval and collaboration hindrances across teams. Traditional documentation methods do not adequately support rapid, multimedia-based knowledge capture and sharing, impacting overall productivity and knowledge consistency.

A mid-sized organization specializing in consulting and training services seeking to enhance internal knowledge sharing and documentation efficiency.

• Implement an AI-powered platform that automatically analyzes and structures video recordings and discussions into coherent, searchable knowledge assets.
• Enable seamless integration of multimedia content with structured text, tags, and hierarchical organization.
• Develop autonomous AI assistants capable of participating in meetings, capturing discussions, and generating summaries to streamline knowledge capture.
• Create a cloud-based, role-based access repository for secure and easy navigation of organizational knowledge.
• Achieve significant time savings in documentation, improve accuracy of knowledge capture, and enhance team collaboration efficiency.

• AI-driven speech analysis and segmentation to convert recordings into organized topics and paragraphs using speech recognition and natural language processing.
• A customizable AI assistant capable of participating in meetings, recording discussions, and producing summarized key points.
• Integration of advanced AI technologies such as speech-to-text engines and content analysis modules for automatic content generation.
• A scalable, cloud-hosted knowledge repository with role-based access control for easy navigation, editing, and sharing.
• Support for multimedia content, including video recordings, with automatic conversion into structured knowledge assets.

• Speech recognition service (e.g., Whisper AI or equivalent) for accurate transcription.
• AI content analysis APIs such as language understanding models.
• Cloud storage solutions for multimedia content hosting.
• Role management and authentication system for secure access control.

• Platform should support at least 10,000 active users with minimal latency.
• Speech recognition accuracy of over 95% in diverse conditions.
• Content retrieval response times under 2 seconds for typical queries.
• Role-based access controls ensuring data security and confidentiality.
• System availability of 99.9% uptime with robust backup and disaster recovery measures.

The platform aims to automate and streamline knowledge capture, resulting in a 30% reduction in documentation time, improved accuracy of stored information, and enhanced collaboration efficiency across teams. These improvements are expected to lead to increased productivity, better knowledge consistency, and faster onboarding processes for new employees.