Production RAG Systems in a Day
Build a retrieval assistant that answers from your own data, with citations
Categories: RAG & Search
Limited-time: use code PAGEWS20 for 20% off · ends 30 Sept 2026
Description
Learning outcomes
- Chunk and embed your own documents so retrieval returns the right passages, not noise.
- Wire a retriever to a language model and ground every answer in sources you can cite.
- Measure retrieval quality with simple evals so you know when the system is good enough to ship.
- Add guardrails so the assistant says it does not know instead of inventing an answer.
What's included
Live session
Learn directly from David in real time, not from a recording.
Recording access
Rewatch for 14 days after each session is delivered.
1-on-1 feedback
Personal review time on your own work.
Maram Guarantee
Your purchase is backed by the Maram Guarantee.
What we'll cover
Module 1. 30 min
- How retrieval works: chunking, embeddings, and vector search
Module 2. 45 min
- Build the pipeline: ingest documents, embed, and retrieve
Module 3. 45 min
- Ground the model in the retrieved passages and add citations
Module 4. 30 min
- Evaluate retrieval quality and add guardrails
Projects
A working retrieval assistant over your own documents that answers questions with cited sources.
Reviews appear here once 3 learners have completed this session.
Do I need a machine learning background?
No. If you can run a Python notebook and use an API key, you can follow along. The focus is on building a working system, not the maths behind the models.
Can I use my own documents?
Yes. Bring a folder of your own documents and you will build the assistant on top of them during the session.
Is the session recorded?
Yes. You get access to the recording for 14 days after the workshop, so you can rebuild the pipeline at your own pace.
What's the refund policy?
Your purchase is backed by the Maram Guarantee.
Your AI Practitioner
David Page
Systems Designer and Vibe Coder
He shipped FreelanceOS, a custom AI-built control centre handling invoicing, job tracking, and expense admin for freelancers. His work sits at the practical end of AI development — turning real workflow pain into working software.
More from David
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