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Local AI training: your data stays with you

Install and use AI on your workstation, without sending data to the cloud. Ollama, AnythingLLM, RAG on your documents. Digital sovereignty starts here.

1 day (7 hours) Eligible for OPCO / FIF-PL funding

Target audienceProfessionals handling sensitive data: regulated professions, finance, legal, HR, healthcare

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What you'll be able to do

Understand how a local LLM works and its privacy advantages

Use Ollama to interact with different AI models locally

Choose the right model for each type of task

Use an AI agent to interact with local documents via RAG

Apply prompting best practices for relevant results

Programme

  1. Session 1

    Why local AI + setup

    • Cloud vs local: what goes online vs what stays with you
    • Installing Ollama and downloading models
    • Installed models: Mistral (French), Qwen 3.5 (reasoning)
    • First test: asking a question to a local model
  2. Session 2

    AnythingLLM: AI with a real interface

    • Installing and configuring AnythingLLM
    • Creating your first workspace
    • Asking business questions in the interface
    • Comparing models: Mistral vs Qwen
  3. Session 3

    Writing effective prompts

    • The winning structure: context → role → task → format → constraints
    • Before/after examples on your use cases
    • Configuring a system prompt in AnythingLLM
    • Writing 5 optimised prompts for your recurring tasks
  4. Session 4

    Working on your documents with RAG

    • RAG: AI reads your documents and answers with sources
    • Drag and drop a full folder into a workspace
    • Querying documents: extraction, summary, cross-referencing
    • Producing a summary note from multiple documents
  5. Session 5

    Organising daily use

    • Creating workspaces per client folder
    • Decision tree: local vs cloud by sensitivity
    • Daily launch procedure
    • Demo of advanced tools: Claude Code + Ollama, AnythingLLM

Practical information

Duration

1 day (7 hours)

Target audience

Professionals handling sensitive data: regulated professions, finance, legal, HR, healthcare

Prerequisites

Regular use of a computer (Mac or PC). No programming skills required.

Group size

1 to 4 people

Teaching approach

100% hands-on on the trainee's workstation. The trainer installs and configures, the trainee learns to use. Exercises on real or fictional documents adapted to the role.

Assessment

Entry-level assessment, practical exercises, end-of-training knowledge evaluation.

Trainer

Colombani.ai, AI consultant and trainer.

Booking lead time

At least 2 weeks between enrolment and the start of training.

Funding

Qualiopi-certified provider (training provider registration number 11757549975): OPCO or FIF-PL support can be requested. The decision rests with the funding body, based on your sector, its criteria and its budgets. Colombani.ai prepares the application with you.

Pricing by quotation, charged per group rather than per person, according to the format, group size and level of expertise. OPCO or FIF-PL funding is available. The amount payable after funding is often well below the list price.

Discuss this course (30 min) OPCO funding is discussed during the call.

Accessibility

This course is accessible to people with disabilities. Contact the disability officer in advance to discuss possible adjustments.

Ulysse Trin, [email protected]

Post-training support

✓ Installed and configured environment: Ollama + models + AnythingLLM
✓ Personalized getting started guide (PDF)
✓ AnythingLLM workspace configured with adapted system prompt
✓ Training completion certificate

Frequently asked questions

Do I need a powerful computer to run local AI? +

A recent computer with 8 GB of RAM is enough for lightweight models (Mistral 7B, Qwen 3.5). For larger models, 16 GB is recommended. We check compatibility beforehand.

Does my data really stay on my machine? +

Yes, 100%. Ollama and AnythingLLM run entirely locally. No data is sent over the internet. That's the whole point of local AI.

Is local AI as powerful as ChatGPT? +

For most business tasks (summarisation, extraction, writing), local models give excellent results. The training teaches you to choose the right model for each task.

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