Build a Grounded Banking Policy Copilot with RAG and Vector Search
Group: Use Case
Product Category: AI Engineering
Sub Category: AI Engineer
Solution Available
Source code, datasets, and other related files for the solution will be provided.
About this Product
Service agents at Cedarline Bank spend long minutes searching policy documents to answer questions about KYC documents, account opening, address changes, dormant accounts, card replacement and fees, and their answers vary from one agent to the next. In this lab you build Cedarline Assist, a retrieval augmented policy copilot that answers only from the approved policy corpus. You build the pipeline end to end: a loader that validates front matter, a word window chunker with overlap and heading metadata, an idempotent indexer backed by a persistent vector store, and a retriever that uses local sentence embeddings and filters chunks by the caller's role. A grounding gate refuses questions when the evidence is weak, and every answer cites the exact chunks it was built from. Restricted documents stay hidden from agent roles and visible to supervisors, and a bearer token decides the role. You then run a retrieval evaluation against a labelled question set, rejecting malformed rows, and report hit rate at k, mean reciprocal rank and refusal accuracy. A chunk size sweep shows how the setting changes results, which gives you a concrete story about trade offs. The lab practises chunking, embeddings, vector database use, retrieval evaluation and grounded answer design through a command line interface, backed by passing unit tests. By the end you have a working copilot CLI, an evaluation report and a README you can explain on a whiteboard in an interview and publish in your portfolio.
Resources
The complete Banking Policy Copilot reference solution is available as a downloadable attachment. It provides a working implementation of the requirements defined in the Business Requirements Document (BRD) and can be used as a reference to understand the expected architecture, design, and implementation approach.
Asset Contents:
- Complete working source code
- Core domain models and business logic
- Required design patterns and components
- Supporting services and integrations, where applicable
- Tests and validation, where applicable
- Runnable examples or demonstration scripts, where applicable
- Configuration and supporting utilities
- Project documentation and setup instructions
Topics
Skills
Languages
English
Level
Intermediate
Business Domain
Banking and Customer Accounts
Project Mentors
Labs • Projects • Practice
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