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.
By Packt Publishing · Refunds up to 10 days before
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.
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.
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.
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.
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.
Six modules covering the privacy-first local AI assistant architecture.
Understand the Gateway, channels, and skills architecture. Set up and configure OpenClaw locally from scratch.
Run and manage local LLMs using Docker Model Runner. Pull models, configure memory, and understand the OpenAI-compatible API.
Configure DM pairing, allowlists, sandbox mode, and proper access controls for your local AI deployment.
Deploy your AI assistant to real messaging platforms without sending data to any third party cloud service.
Design an extensible assistant architecture. Add skills, configure personality, and set up proactive automation.
Deploy your OpenClaw and Docker setup to a VPS for always-on availability running 24 hours a day.
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
Rami Krispin builds privacy-first AI systems in production using Docker and open weight models.
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.
Privacy-conscious developers who want capable AI without compromising on data privacy.
Everything privacy-conscious developers need to know about local AI data handling.
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.
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.
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.
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.
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.
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.
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