Enterprise AI12 weeks · 2024

Enterprise Client

Building an AI That Actively Participates in Enterprise Meetings

The Challenge

Enterprise teams needed an AI presence in meetings that could listen, speak, see shared content, answer questions with business context, and generate dynamic visualizations — all in real-time with sub-second latency.

Our Approach

We architected a model-agnostic AI meeting participant with a multi-MCP plugin system. Real-time audio via WhisperLive STT and ElevenLabs TTS, Gemini vision for screen comprehension, and a 3-tier memory architecture (Redis + Qdrant + PostgreSQL) for persistent context.

Results Delivered

27+
27+

AI-callable tools across data, content, and visualization

Multi-model
Multi-model

Claude and Gemini support with seamless switching

Real-time
Real-time

Sub-second STT/TTS with continuous listening

Technology Stack

PythonFastAPITypeScriptClaude APIGemini APIElevenLabsRedisQdrantPostgreSQLDockerMCP

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