Kaizan
The Client Intelligence Platform to retain and grow your client revenue.
MeetEva represents the 2026 evolution of AI meeting intelligence, moving beyond simple transcription into the realm of autonomous executive assistance. Built on a proprietary ensemble of transformer models optimized for noise-robust audio processing, MeetEva functions as a 'Chief of Staff' that attends virtual meetings on platforms like Zoom, Teams, and Google Meet. Its technical architecture utilizes advanced diarization to distinguish between up to 15 speakers in complex acoustic environments, achieving a 98.4% accuracy rate in multi-accent scenarios. Unlike its predecessors, MeetEva focuses on 'Intent-Based Analysis,' which allows it to distinguish between casual banter and binding commitments. In the 2026 market, it stands out through its deep integration with enterprise stacks, automatically updating CRM fields in Salesforce or HubSpot and triggering Jira tickets based on verbal consensus. Its security infrastructure supports end-to-end encryption and localized data residency, making it a viable solution for legal and financial sectors where data privacy is non-negotiable. By leveraging RAG (Retrieval-Augmented Generation), MeetEva can surface context from previous meetings during a live session, providing the user with real-time briefing notes and historical context.
Uses vocal biometric profiling to identify speakers even when participating from the same physical room/microphone.
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.
LLM-driven parser that differentiates between conditional statements and confirmed commitments.
Utilizes a vector database (RAG) to link related discussions across months of meeting history.
Analyzes pitch, pace, and linguistic markers to measure participant engagement and sentiment shifts.
Provides live transcription-based prompts to the user's screen during sales calls.
Directly maps meeting entities like 'Price', 'Timeline', and 'Decision Maker' to CRM fields.
Automatically identifies and masks sensitive data like credit card numbers or addresses in transcripts.
Sales reps forget to update the CRM with specific client pain points.
Registry Updated:2/7/2026
Generates follow-up email draft.
Action items discussed in stand-ups are frequently lost or not tracked.
Manual court reporting is slow and expensive for preliminary discovery.