Kaizan
The Client Intelligence Platform to retain and grow your client revenue.
The AI-powered sous-chef for your meetings, delivering gourmet summaries and actionable insights.
MeetBistro is an advanced AI meeting intelligence platform engineered to transform raw conversational data into structured, high-utility organizational knowledge. By 2026, its architecture has evolved beyond simple transcription to utilize multi-modal LLM chains that contextually understand project nuances across various industries. The platform functions as a persistent knowledge ledger, integrating directly with the communication stack (Zoom, Microsoft Teams, Google Meet) to capture audio/video streams in real-time. Technically, it employs sophisticated diarization algorithms to distinguish between up to 15 unique speakers with 98% accuracy and uses semantic analysis to categorize meeting segments into themes like 'Technical Roadblocks', 'Commercial Agreements', and 'Strategic Pivots'. Positioned for mid-market and enterprise teams, MeetBistro differentiates itself through its 'Bistro Templates'—pre-configured logic sets that tailor summaries for specific roles, ensuring that a CTO receives architectural impacts while a Product Manager receives user requirement updates from the same recording. Its 2026 market position is defined by its ability to bridge the gap between asynchronous communication and project management tools, effectively turning every meeting into a self-updating documentation source.
Uses RAG (Retrieval-Augmented Generation) to apply specific context to summaries based on historical project data.
The Client Intelligence Platform to retain and grow your client revenue.
Turn messy meeting audio into structured executive summaries and action items instantly.
Enterprise-grade neural speech recognition with hyper-accurate multi-speaker diarization and semantic context mapping.
The AI-Powered Meeting Orchestrator for High-Velocity Teams
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Combines audio fingerprinting and visual cues from video streams to identify speakers in complex environments.
NLP model that cross-references identified tasks with current JIRA or Asana backlogs to prevent duplicate entries.
Tracks speaker emotional tone throughout a session to identify points of friction or high agreement.
Web-socket based real-time alerts when specific pre-defined phrases are mentioned.
Analyzes a series of meetings (e.g., a month of standups) to identify long-term trends and blockers.
Automatic detection and masking of sensitive data (credit cards, PII) in transcripts using regex and NER.
Sales reps forget crucial details during discovery calls, leading to poor follow-ups.
Registry Updated:2/7/2026
Complex technical decisions are discussed but not documented in tickets.
Reviewing hours of depositions for specific testimony is time-prohibitive.