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Twinmind Reference Architecture
ASecurity'Production architecture for meeting AI systems using TwinMind: transcription
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- Added September 21, 2026
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[](https://www.skillsdirectory.com/skills/jeremylongshore-twinmind-reference-architecture-334365ef)---
name: twinmind-reference-architecture
description: 'Production architecture for meeting AI systems using TwinMind: transcription
pipeline, memory vault, action item workflow, and calendar integration.
Use when implementing reference architecture,
or managing TwinMind meeting AI operations.
Trigger with phrases like "twinmind reference architecture", "twinmind reference
architecture".
'
allowed-tools: Read, Write, Edit, Bash(npm:*), Bash(curl:*), Grep
version: 1.13.0
license: MIT
author: Jeremy Longshore <jeremy@intentsolutions.io>
tags:
- saas
- twinmind
- architecture
compatibility: Designed for Claude Code
---
# TwinMind Reference Architecture
## Overview
Production architecture for meeting AI systems using TwinMind: transcription pipeline, memory vault, action item workflow, and calendar integration. TwinMind uses the Ear-3 speech model (5.26% WER, 3.8% DER) for transcription, with GPT-4, Claude, and Gemini for AI summarization.
## Prerequisites
- TwinMind account (Free, Pro $10/mo, or Enterprise)
- Chrome extension installed and authenticated
- Understanding of TwinMind workflow
## Instructions
### Step 1: Setup
TwinMind operates as a Chrome extension and mobile app with optional API access for Pro/Enterprise users.
```javascript
// TwinMind configuration
const config = {
apiKey: process.env.TWINMIND_API_KEY,
model: "ear-3", // Transcription model
aiModels: ["gpt-4", "claude", "gemini"], // Summary models
};
```
### Step 2: Implementation
```javascript
// TwinMind Reference Architecture implementation
// Core TwinMind integration
const twinmind = {
transcriptionModel: "ear-3",
languages: ["en", "es", "ko", "ja", "fr"],
features: ["transcription", "summary", "action-items"],
privacyMode: "on-device", // Audio never stored
};
// Check transcription capabilities
async function verify() {
const health = await fetch("https://api.twinmind.com/v1/health");
console.log("TwinMind status:", await health.json());
}
```
### Step 3: Verification
```bash
# Verify TwinMind integration
curl -H "Authorization: Bearer $TWINMIND_API_KEY" https://api.twinmind.com/v1/health | jq .
```
## Key TwinMind Specifications
| Feature | Specification |
|---------|--------------|
| Transcription model | Ear-3 (5.26% WER) |
| Speaker diarization | 3.8% DER |
| Languages | 140+ supported |
| Audio processing | On-device (no recordings stored) |
| AI models | GPT-4, Claude, Gemini (auto-routed) |
| Platforms | Chrome extension, iOS, Android |
| Pricing | Free / Pro $10/mo / Enterprise custom |
## Output
- TwinMind Reference Architecture configured and verified
- TwinMind integration operational
- Meeting transcription workflow ready
## Error Handling
| Error | Cause | Solution |
|-------|-------|----------|
| Microphone access denied | Browser permissions not granted | Enable in Chrome settings |
| Transcription not starting | Audio source not detected | Check microphone selection |
| API key invalid | Incorrect or expired key | Regenerate in TwinMind dashboard |
| Sync failed | Network interruption | Check connection, retry |
| Calendar disconnect | OAuth token expired | Re-authorize in Settings |
## Resources
- [TwinMind Website](https://twinmind.com)
- [Chrome Extension](https://chromewebstore.google.com/detail/twinmind/agpbjhhcmoanaljagpoheldgjhclepdj)
- [Ear-3 Model](https://www.marktechpost.com/2025/09/11/twinmind-introduces-ear-3-model/)
- [iOS App](https://apps.apple.com/us/app/twinmind-ai-notes-memory/id6504585781)
## Next Steps
See `twinmind-prod-checklist` for production readiness.
## Examples
**Basic**: Configure reference architecture with default TwinMind settings for standard meeting workflows.
**Enterprise**: Customize for high-volume meeting transcription with monitoring and alerting.
Files in this skill
- SKILL.md
- references/implementation.md
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