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# AI Concierge – Technical Overview

# 1. Overview

AI Concierge is a domain-specific conversational AI agent designed for secure deployment within trusted enterprise environments. It supports both browser-based and on-premises use cases and is tailored for organizational functions such as HR helpdesks, IT support, and compliance Q&A.

The platform operates on enterprise-specific data and runs open-source large language models, including:

  • Llama 4 Maverick: Customer service, general Q&A, multilingual agents
  • Deepseek R1 70B: Developer support, code generation, documentation bots
  • Llama 3.3 70B: Legal, HR, writing-intensive tasks, or any scenario needing high linguistic precision

AI Concierge is ideal for teams building AI copilots, automating tasks, or integrating LLM-powered tools into business operations.

# 2. Data Privacy & Security

AI Concierge is engineered with a privacy-first architecture:

  • User interactions are not stored, logged, or used for model retraining.
  • Session data remains local—either in the user's browser or customer-controlled infrastructure.
  • No telemetry, analytics, or backend monitoring is included by default.
  • Internal administrators cannot view user chat history or prompt content.

This closed-loop model supports use in regulated industries like healthcare, finance, and government.

# 3. Key Features

# 🔒 Privacy-First Design

  • No data is stored on central servers or used for retraining.
  • Conversations are processed in-session and stored locally.
  • Enables safe use in regulated industries.

# 🏢 Enterprise-Scoped AI

  • Tailored for internal functions like HR, IT, and compliance.
  • Deployed via UI or API within your trusted runtime.
  • Grounded in your proprietary enterprise data.

# 💬 Persistent and Seamless UX

  • Chat history is saved in-browser, not in the cloud.
  • Sessions persist until explicitly cleared.
  • Revisit previous prompts via a built-in history log.

# 🚀 Lightweight, Flexible Deployment

  • Runs in-browser with no infrastructure required.
  • Also supports hybrid or on-premise setups.
  • Ideal for pilot projects and internal copilots.

# 🔧 Open-Source Model Backbone

  • Powered by Llama 3.3 and DeepSeek-R1.
  • Models are customizable to your use case and data.
  • Future support planned for model switching in-session.

# 🧪 Free Trial Access

  • Includes:
    • Serverless Endpoints for model serving
    • Model Execution & Indexing Units (MEIUs) including Retrieval-Augmented Generation (RAG)
  • Best for teams with predictable usage patterns.

# 4. Accessing the Platform

  1. Create or receive a user account.

Tip: If you need help, visit our documentation to create an account or receive a user account.

  1. Select an access tier:
    • Trial version
    • Production deployment
  2. Log in to the platform:
    • Trial – DeepSeek R1
    • Production – DeepSeek R1

After login, the chat interface will load automatically.

# 5. User Interface Overview

UI Element Description
Chat History View and revisit past prompts. See: Chat History
Clear Window Clears the current window while retaining session memory.
Start New Conversation Resets chat context and removes any attached PDFs.
Document Upload Upload up to 3 PDFs (max 1MB each) for RAG-based context. See: Attach File
Generate Button Submits the current prompt to the selected model.
Save Conversation Stores the current chat session locally in the browser.
Download PDF Exports the conversation transcript as a PDF file.
Copy to Clipboard Copies the most recent prompt and response to your clipboard.
Account Menu Manage team access, user profile, and terms/policies.

# 6. Supported Browsers

  • Google Chrome / Microsoft Edge
  • Mozilla Firefox
  • Apple Safari

# 7. Tips for Best Results

  • Upload .PDFs to enable Mini-RAG-style context injection.
  • Maximum: 3 files per session, each under 1MB.
  • Hover over a file to remove it (click the “X”).
  • For better outputs:
    • Be specific (e.g., “Explain how AI is used in radiology”).
    • Break complex questions into steps.
    • Add background/context when necessary.

Refer to the Meta Llama 3 Prompt Format Guide for advanced prompt structuring.

# 8. Security & Data Protection

  • All chat history is stored in your browser only.
  • Uploaded documents are deleted when history is cleared.
  • For extra data protection:
    • Enable disk encryption (e.g., BitLocker for Windows, FileVault for macOS).
    • Always log out on shared or public systems.

# 9. Troubleshooting

Issue Recommended Action
UI is slow or unresponsive Refresh the page or check the Phoeniqs Status Page.
File won’t upload Ensure it’s a .pdf file under 1MB; maximum of 3 files per session.
Poor response quality Rephrase your prompt; try using specific or multi-step questions.
Session reset unexpectedly Confirm browser storage is enabled; avoid private/incognito mode.

For questions or support, contact your system administrator or the technical support team.

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