AI you can trust, on hardware you own
You can get real AI value without handing your documents, customer data, and internal knowledge to a third-party chatbot. A local model keeps all of it on your own hardware — and it can be dramatically cheaper at scale.
This session skips the web-chatbot hype and builds private, practical AI: local models, your own documents, and agents wired into the tools you already use.
What you'll walk away with
- Local language models running with Ollama, fronted by Open WebUI.
- A model and hardware choice that fits your budget and workload.
- Retrieval workflows (RAG) that answer questions from your own documents.
- Task-specific agents and internal tools, not just a chat window.
- A clear read on when cloud APIs still make sense and when they don't.
- Real cost math versus per-token API pricing.
The session, in order
- How local LLMs work, in plain language
- Ollama and Open WebUI: your first private assistant
- Models and hardware that actually fit your use case
- RAG: asking questions of your own documents
- Task-specific agents and internal tools
- Privacy, cost, and a clinic for your own AI use case
Who it's for
Owners and technical leads who want AI capability without the privacy and cost of sending everything to a third party.
Built on three priorities
Privacy first, security first, and data ownership first. You leave with systems you control, running on infrastructure you own.
What you get
Exclusive materials for registrants, including the session recording and hands-on walkthroughs.
- Model guide — which models fit which budgets and tasks (coming soon)
- RAG setup — connect your documents to a private assistant (coming soon)
- Session recording — posted here after the live session