TAG ARCHIVE
meeting-ai
MARIA OSブログのmeeting-aiタグに関連する3件の記事。ボンギンカンの判断OS、AIガバナンス、Agentic Company研究をテーマ別に参照しやすい技術記事アーカイブです。
判断OS / 決断インテリジェンスOS
組織の判断を実行可能な意思決定システムに変換するMARIA OS中核研究。
エージェント型企業アーキテクチャ
人間とエージェントの組織、委任境界、役割トポロジー、ガバナンス付き自律性に関する研究。
責任ゲートとAIガバナンス
AIエージェントの安全性、説明責任、フェイルクローズドゲート、監査可能性、HITL制御。
マルチエージェント数学
収束、安定性、ゲーム理論、グラフダイナミクス、マルチエージェント評価の形式モデル。
エビデンス、RAG、ナレッジガバナンス
エビデンスバンドル、検索アーキテクチャ、Graph RAG、ナレッジトラスト、監査可能な推論パイプライン。
Agentic R&Dと判断科学
研究運用、シミュレーションラボ、判断科学、再帰的改善、実験的AIガバナンス。
Gated Meeting Intelligence: Fail-Closed Privacy Architecture for AI-Powered Meeting Transcription
Designing consent, scope, and export gates that enforce data sovereignty before a single word is stored
When an AI bot joins a meeting, the first question is not 'what was said?' but 'who consented to recording?' This paper formalizes the gate architecture behind MARIA Meeting AI — a system where Consent, Scope, Export, and Speak gates form a fail-closed barrier between raw audio and persistent storage. We derive the gate evaluation algebra, prove that the composition of fail-closed gates preserves the fail-closed property, and show how the Scope gate implements information-theoretic privacy bounds by restricting full transcript access to internal-only meetings. In production deployments, the architecture achieves zero unauthorized data retention while adding less than 3ms latency per gate evaluation.
Evidence-Linked Meeting Minutes: Structured Extraction with Mandatory Citation Chains
Every decision must cite its source — how MARIA Meeting AI eliminates hallucinated minutes through segment-level evidence linking
Traditional meeting minutes suffer from a fundamental trust problem: the reader cannot verify whether a recorded decision actually occurred in the meeting or was interpolated by the note-taker. MARIA Meeting AI solves this by enforcing mandatory evidence linking — every decision, action item, and summary section must reference specific transcript segments as evidence. This paper formalizes the evidence-linking constraint, presents the incremental summarization algorithm that generates minutes every 15 seconds during live meetings, and proves that the citation coverage metric converges to completeness as transcript length increases. In evaluated Japanese business meetings, the system achieved 94% citation coverage with zero hallucinated decisions.
Real-Time Meeting Session Orchestration: State Machine Design for Multi-Component Bot Systems
How a seven-state machine coordinates browser automation, audio capture, speech recognition, and live streaming into a coherent meeting intelligence pipeline
A meeting AI bot is not a single component — it is an orchestra of subsystems that must start, coordinate, and stop in precise sequence. The browser must launch before audio can be captured. Audio must flow before speech recognition begins. Recognition must produce segments before minutes can be generated. And when the meeting ends, all components must shut down gracefully without losing data. This paper presents the state machine design of MARIA Meeting AI's session manager, which coordinates Playwright browser automation, CDP audio capture, Gemini Live Audio ASR, and incremental minutes generation through a seven-state lifecycle with EventEmitter-based real-time streaming to dashboard clients.