Build a Governed RAG Pricing Copilot with Python and FastAPI
Group: Use Case
Product Category: AI Engineering
Sub Category: RAG & LLM Applications
Solution Available
Source code, datasets, and other related files for the solution will be provided.
Prerequisites
About this Product
Retail teams ask pricing and promotion rules every day, and one wrong answer costs margin and creates regulatory exposure.
What you build
- Governed ingestion: policy documents load with tenant, region, version and effective dates, and poisoned documents are quarantined.
- Hybrid retriever: keyword and vector search, filtered by tenant and region before ranking.
- Grounded answerer: cited answers that omit expired documents and refuse when the evidence is weak.
- Guardrails and audit: PII redaction, injection defense, role gating and a hash chained audit log with a verifier.
Skills you practise
- Enterprise RAG: hybrid retrieval, chunking and cited, grounded answers.
- Knowledge architecture: per tenant and region indexes with versioning and supersession.
- Context engineering: budgeted, ranked and deduplicated context that treats retrieved text as data.
- Adversarial evaluation: an attack suite with a release gate that requires zero leaks.
Outcome
- Release ready copilot: a tested FastAPI service with an evaluation report you can explain in an interview and show in your portfolio
Interview Q&A Included
1 practice set bundled with this lab
-
Governed RAG Pricing Copilot Assessment
Category: AI Engineering Subcategory: AI Agent Engineer 48 questionsThis assessment checks what you learned while building and testing a governed retrieval augmented pricing copilot. It has five groups: scenario and requirements, retrieval and context design, guardrails and governance, …
Resources
Step by step instructions to install, configure and run the copilot on Windows and macOS.
- What to install first, with the commands to check each tool
- Creating the virtual environment and installing the dependencies
- Running setup, which builds the region indexes from the sample documents
- Starting the API and sending your first question
- Running the tests and the evaluation suite
- Fixes for the most common setup problems
Topics
Skills
Languages
English
Level
Expert
Business Domain
Retail and E-commerce Pricing and Promotions
Project Mentors
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