Real-Time Meeting Agent
Real-time AI Meeting agent which reduces meeting follow-up time by 75%
<2 second latency
for real-time transcription
90% accuracy
in agenda progress tracking
3-5 actionable insights
generated per 15-minute segment
What I Built
Three-layer architecture - speech recognition, natural language understanding, and intelligent analysis
Four core capabilities - real-time transcription, automatic insight extraction, agenda progress tracking, and proactive suggestions
The Meeting Intelligence Gap
The problem isn't only the meetings themselves, but the cognitive overhead required to capture, synthesize, and act on what was discussed.
Information Loss - Critical decisions and action items get lost in conversation flow
Cognitive Overload - Participants can't fully engage while trying to take notes
Delayed Insights - By the time meeting notes are reviewed, context is lost
No Real-Time Guidance - Meetings drift off-topic without immediate feedback
Selecting The Right Approach
The system processes audio in real-time, transforming raw speech into structured intelligence that helps teams stay focused and capture value
Audio Input
Whisper API
LLM Analyses
Real-time UI
Core Capabilities
Built on a three-layer architecture combining speech recognition, natural language understanding, and intelligent analysis
Real-Time Transcription
Sub-second audio-to-text conversion that handles overlapping speech, multiple speakers, and background noise effectively
Groq Whisper API + Stream Processing
Intelligent Insight Extraction
Automatically identifies decisions, commitments, and key information using context-aware prompts that filter out fluff
Custom LLM Prompts + Context Windows
Agenda Progress Tracking
Real-time semantic matching against agenda items to keep meetings on track and ensure all key topics are covered
Semantic Search + State Management
Proactive Suggestions
Generates real-time recommendations, questions, and warnings to prevent off-topic drift and missed opportunities
Multi-class Classification
Performance Benchmarks
<2s Latency
Audio to transcript
95%+ Parse Rate
LLM response parsing
99.2% Uptime
API reliability
87% Dedup Rate
Duplicate reduction
Technologies Used
Technologies
Machine Learning & AI
Hands-on experimentation with fraud detection, retrieval systems, and autonomous agents.
