Local AI Data Privacy · For Developers · April 26

Local AI With Complete Data Privacy — Built for Privacy-Conscious Developers

Developers who care about data privacy should not have to compromise on AI capability. This live workshop shows you how to build a local AI assistant with complete data privacy using OpenClaw and Docker Model Runner — no data leaves your machine during AI processing.

Sunday, April 26   9am to 1pm EDT
4 Hours   Hands-on coding
Live Online   Interactive

Workshop Details

📅
Date and Time
Sunday, April 26, 2026
9:00am to 1:00pm EDT
Duration
4 Hours · Hands-on
💻
Format
Live Online · Interactive
🎓
Includes
Certificate of Completion
🔒
Privacy
100% Local · No Cloud Required
Register on Eventbrite →

By Packt Publishing · Refunds up to 10 days before

OpenClaw — 200K+ GitHub Stars
4 Hours Live Hands-On Coding
✦ By Packt Publishing
No Cloud Dependency Required
Certificate of Completion
Why Trust Packt

Over 20 Years of Helping Developers Build Real Skills

7,500+
Books and video courses published for developers worldwide
108
Live workshops and events hosted on Eventbrite
200K+
GitHub stars for OpenClaw — the tool you will master
100%
Hands-on — every session involves real code and live building
About This Workshop

Why Data Privacy Should Drive Your Local AI Stack Choices

Privacy-conscious developers cannot use cloud AI for sensitive tasks. This workshop builds the alternative — a local AI stack with provable data privacy where you control everything from the model weights to the conversation storage.

🖥

What is OpenClaw?

OpenClaw is the open-source personal AI assistant that went viral in early 2026 with 200K+ GitHub stars. It runs on your own devices and connects to WhatsApp, Telegram, Slack and more. No subscription. No data leaving your machine.

🐳

What is Docker Model Runner?

Docker Model Runner is Docker's native feature for running large language models locally on your machine. It gives you an OpenAI-compatible API that OpenClaw uses as its AI brain — complete data privacy, no cloud costs.

🔗

Why Combine OpenClaw and Docker?

OpenClaw gives you the assistant interface and messaging integrations. Docker Model Runner gives you the AI brain running privately on your machine. Together they create a production grade private AI assistant you fully own.

🎯

Why Attend as a Live Workshop?

Setting this up from scattered documentation takes days of debugging. This live workshop gives you a complete guided build in 4 hours with a live instructor answering your questions. Packt has delivered 108 workshops worldwide.

Workshop Curriculum

Building a Local AI System With Complete Data Privacy

Six modules covering the privacy-first local AI assistant architecture.

01

How OpenClaw Works

Understand the Gateway, channels, and skills architecture. Set up and configure OpenClaw locally from scratch.

02

Docker Model Runner Setup

Run and manage local LLMs using Docker Model Runner. Pull models, configure memory, and understand the OpenAI-compatible API.

03

Security and Privacy

Configure DM pairing, allowlists, sandbox mode, and proper access controls for your local AI deployment.

04

Connect to WhatsApp or Telegram

Deploy your AI assistant to real messaging platforms without sending data to any third party cloud service.

05

Scalable Architecture

Design an extensible assistant architecture. Add skills, configure personality, and set up proactive automation.

06

Production Deployment

Deploy your OpenClaw and Docker setup to a VPS for always-on availability running 24 hours a day.

What You Walk Away With

By the End of This Workshop You Will Have

A local AI assistant with complete data privacy — built and verified.

A fully functional local AI assistant running on your machine

Docker Model Runner configured with your chosen LLM model

OpenClaw connected to WhatsApp or Telegram

Security and privacy configuration you can trust

A reusable architecture for future AI assistant projects

Certificate of completion from Packt Publishing

Your Instructor

Learn Privacy-First Local AI From a Docker Captain

Rami Krispin builds privacy-first AI systems in production using Docker and open weight models.

Rami Krispin

Rami Krispin

Workshop Instructor · April 26, 2026

Rami is a Senior Manager of Data Science and Engineering, Docker Captain, and LinkedIn Learning Instructor with deep expertise in building and deploying production AI systems. He guides you step by step from a blank terminal to a fully deployed private AI assistant — answering your questions live throughout the 4-hour session.

Prerequisites

Who Is This Workshop For?

Privacy-conscious developers who want capable AI without compromising on data privacy.

Frequently Asked Questions

Common Questions About Local AI Data Privacy for Developers

Everything privacy-conscious developers need to know about local AI data handling.

What data privacy guarantees does a local AI setup provide? +

A local AI setup with Docker Model Runner and OpenClaw provides these guarantees: AI inference data never leaves your hardware, conversation content is not stored by any third party, model weights are downloaded once and then run entirely locally, and no usage analytics or telemetry is sent to AI providers. These are stronger privacy guarantees than any cloud AI service can offer.

How does local AI data privacy compare to cloud AI with encryption? +

Cloud AI with encryption protects data in transit but the data is still decrypted and processed on the cloud provider's servers. Local AI data privacy means the data never leaves your hardware at all — not even in encrypted form to an external server. This is a fundamentally stronger privacy model that no cloud AI service can match.

Can I use a local AI assistant for processing confidential client data? +

Running AI locally with OpenClaw and Docker Model Runner means client data is processed entirely on your own hardware. This is substantially safer than using cloud AI services for confidential client data. For formal compliance advice, consult a legal professional familiar with your specific industry regulations.

What privacy risks remain with a local AI setup? +

The main remaining privacy considerations are: your operating system and Docker Desktop may collect some usage telemetry (configurable), messaging platforms like WhatsApp handle message delivery through their servers, and model downloads come from Docker Hub. The AI inference itself — which is where your actual conversation content is processed — is completely local and private.

How do I explain the data privacy of my local AI setup to non-technical stakeholders? +

A simple explanation: your conversation goes from your messaging app to your own computer, the AI on your computer processes it and generates a response, the response goes back through your messaging app. At no point does your conversation content travel to any AI company's servers. The instructor covers how to explain and document this data flow during the workshop.

Can I configure my local AI assistant to delete conversation data automatically? +

OpenClaw's conversation handling can be configured for your privacy requirements. The instructor covers conversation storage options and how to configure automatic deletion or minimal data retention during the workshop — giving you control over exactly how much conversation data your local AI assistant stores.

Local AI Data Privacy for Developers · April 26, 2026

Ready to Build Local AI With Complete Data Privacy?

4 hours. Live instructor. Privacy-first local AI assistant by the end. Seats are limited.

Register Now →

Sunday April 26 · 9am to 1pm EDT · Online · Packt Publishing