L.I.F.E AI Enhancer — Secure Copilot & Azure AI for Regulated Teams

Prove, optimize, and govern Copilot-driven workflows in finance, health, and education.

• One-click engine learning & optimization report — L.I.F.E Theory benchmarks with Φ proto-consciousness metrics, Venturi 3-Gate analysis, and learning velocity trends.
• Guardrails for Copilot and Azure OpenAI in regulated repos — Policy checks, real-time telemetry, and suggestion-quality governance for teams handling sensitive data.
• Evidence-ready metrics — 97.3% accuracy, <0.38 ms latency, learning velocity trends, and energy efficiency validated against ISO-style audit requirements.
• Free to start — 30 optimisations per day with no account, keys, or config required.

⬇️ Install Now — Works on Desktop, Tablet & Mobile

📱 On a tablet or phone? Tap the green "Open in VS Code Web" button above — it opens a full VS Code editor in your browser where you can install and use L.I.F.E immediately. No desktop needed.

💻 On desktop? Tap "Install in VS Code" or paste this in your terminal:

code --install-extension LIFEAIEnhancer.life-ai-enhancer

What you get — immediately, no setup required

• Verify Copilot usage is safe — Real-time policy checks flag suggestions that violate your team's compliance rules before they reach the codebase.
• Run L.I.F.E engine learning report — One command generates a full optimization report with Venturi gate scores, Φ consciousness index, and learning velocity.
• Export evidence for audits — Download timestamped metrics (accuracy, latency, energy efficiency, acceptance trends) as structured data for regulatory submissions.

NEW in v1.1.0 — Microsoft sign-in: One-click authentication via your Microsoft account. Unlimited optimisations for signed-in users, live metrics, and API key stored securely in VS Code. Free tier still available with 30 optimisations/day and no account required.

L.I.F.E is an enhancement layer that works alongside Azure AI, GitHub Copilot, VS Code, and other Microsoft tools — not a replacement.

Why regulated teams choose L.I.F.E

Disclaimer: This is an independent third-party extension. Not affiliated with, endorsed by, or sponsored by Microsoft Corporation, GitHub, Inc., or OpenAI. Works alongside GitHub Copilot, Azure OpenAI Service, Microsoft 365 Copilot, Cursor, Claude, and other AI coding tools.

Pricing

Free tier resets daily at midnight. Power users who hit the limit see upgrade prompts.

Lock in Early Bird pricing →

Platform Screenshots

L.I.F.E Platform — Live Dashboard

Self-Learning Feedback

Rate every suggestion with Accept / Reject / 1–5 stars — the system learns your preferences and suppresses low-quality patterns automatically.

Metrics Dashboard

Recommend to Your Team

Add this to your repo's .vscode/extensions.json and VS Code will prompt every team member to install L.I.F.E automatically:

{
  "recommendations": [
    "LIFEAIEnhancer.life-ai-enhancer"
  ]
}

Who is L.I.F.E for?

• Regulated teams (finance, health, education) — Prove AI usage is compliant; export evidence for auditors and governance boards.
• Azure & Microsoft developers — Azure Functions, DevOps, Microsoft Graph, Power Platform, Bicep/ARM — governed by L.I.F.E guardrails.
• Engineering orgs (10–500 engineers) — Team analytics, Entra ID SSO, GDPR/CCPA-compliant metrics, suggestion-quality SLAs.
• Any developer using AI code assistants — Python, TypeScript, JavaScript, C#, .NET in VS Code.
• Research & academia — Free Developer tier for academic research and coursework.

Azure & Microsoft Ecosystem Integration

L.I.F.E is built for developers already working inside the Microsoft ecosystem. It enhances — never replaces — your existing tools:

Already on Azure? L.I.F.E runs on the same subscription, in the same region, with the same identity provider. Zero friction onboarding for Azure-native teams.

How it works

1. You code — the extension watches your accept/reject patterns locally in VS Code.
2. L.I.F.E optimises — your patterns are sent (TLS 1.3) to the Venturi 3-Gate engine which filters suggestions in <0.4 ms.
3. You rate — Accept / Reject / 1–5 stars feeds the self-learning loop; quality improves with every session.
4. Optional EEG — connect Quest 3, Emotiv EPOC, Muse 2, or OpenBCI to adapt suggestion complexity to your real-time cognitive state.

Code context is held in-memory for <1 second and never persisted to disk on L.I.F.E servers.

For full technical documentation, API reference, and Azure integration guides visit the platform:

Open L.I.F.E Platform Docs →

Privacy & Security

Full Privacy Policy →

Installation

Desktop (Windows, macOS, Linux)

1. Open VS Code → Extensions (Ctrl+Shift+X)
2. Search "L.I.F.E AI Enhancer"
3. Click Install

Or from the command line:

code --install-extension LIFEAIEnhancer.life-ai-enhancer

Tablet & Mobile (iPad, Android, Chromebook)

1. Open VS Code for Web in your browser
2. Click Install on the extension page
3. Start coding — L.I.F.E works in VS Code Web with full functionality

Tip: Bookmark vscode.dev — it's a full VS Code editor that runs entirely in your browser on any device.

Requirements: VS Code 1.95.0+ (desktop) or any modern browser (web). Internet connection required.

Unlock unlimited optimisations

1. Ctrl+Shift+P → L.I.F.E: Sign In with Microsoft
2. Authenticate with your Microsoft account (one click)
3. Done — your API key is generated and stored securely in VS Code

Choose a plan on Microsoft Marketplace →

Quick Start

1. Install from VS Code Marketplace
2. Open any code file — L.I.F.E starts optimising immediately
3. Check the status bar — L.I.F.E: Free (3/30 today) shows your daily usage
4. Rate suggestions — Accept / Reject / 1–5 stars to train the self-learning engine

Keyboard shortcuts

Documentation, FAQ & API Reference

All technical documentation, API integration guides, SDK examples, troubleshooting, and FAQs live on the L.I.F.E Platform so you always have the latest version:

Open L.I.F.E Platform → · API Docs → · FAQ →

LIFE Theory Language Server (Copilot MCP)

This project includes a custom MCP server that exposes the live L.I.F.E engine to GitHub Copilot, Claude, and other agents that speak the Model Context Protocol.

Python environment

# From the repo root
python -m venv .venv
# Windows
.\.venv\Scripts\activate
# macOS / Linux
source .venv/bin/activate

pip install -r requirements.txt

MCP configuration

The .vscode/mcp.json in this repo points at a cross-platform wrapper script that auto-detects the correct Python interpreter:

{
  "servers": {
    "life-theory": {
      "type": "stdio",
      "command": "${workspaceFolder}/vscode-extension/life-ai-enhancer/.github/copilot/Copilot/run_life_theory_server",
      "args": [],
      "cwd": "${workspaceFolder}/vscode-extension/life-ai-enhancer/.github/copilot/Copilot",
      "env": {
        "LIFE_API_URL": "https://life-ai-enhancer.orangecliff-2effc296.uksouth.azurecontainerapps.io"
      }
    }
  }
}

Platform notes

The wrapper scripts resolve the virtual-environment interpreter for each OS:

• Windows: prefers .venv\Scripts\python.exe
• macOS / Linux: prefers .venv/bin/python
• Fallback: python on PATH if no virtual environment is found

No manual changes to the MCP config are needed when switching between platforms.

Known Limitations

• VS Code only — more editors coming soon
• Best language support: Python, TypeScript, JavaScript, C# (Go/Rust/C++ improving)
• Internet required for AI suggestions (offline: syntax highlighting continues)
• Free tier: 30 optimisations/day, resets at midnight
• EEG hardware: Quest 3, Emotiv EPOC+, Muse 2, OpenBCI supported; Legacy Muse (2014) and NeuroSky MindWave not supported

Support

• Platform & Docs: lifecoach-121.com
• Email: Info@lifecoach-121.com
• Issues: GitHub Issues

License

PROPRIETARY — PATENT PENDING

COPYRIGHT © 2024–2026 Sergio Miguel Paya Borrull, L.I.F.ECoach121.com Limited. All Rights Reserved.

Patent: GB2519103.2 — Venturi 3-Gate System, 14 Core Equations, 12-Section Architecture, Neuroadaptive Learning Algorithms.

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