AI Powered Government Permit Application Assistant with RAG and Vector Search
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.
About this Product
AI Powered Government Permit Application Assistant with RAG and Vector Search is an intermediate-level, Python CLI product that builds a context-aware question answering system for a government permit office — retrieving policy chunks from a local vector database, enriching answers with the citizen's own case record, and generating cited replies that refuse when evidence is weak.
With this product, you'll build a CLI application that can:
- Ingest government policy documents into a local ChromaDB vector database with heading-aware chunking and idempotent re-runs
- Retrieve top-k policy chunks using cosine similarity with metadata filtering — refusing automatically when evidence falls below the minimum score
- Enrich answers with live case context — appointment dates, case stage, and hold reasons come only from the case record, never from model memory
- Generate grounded, cited replies where every claim references a retrieved chunk ID — missing citations trigger a retry then a refusal
- Evaluate retrieval quality across two chunking configurations using hit@k, MRR, faithfulness, and refusal accuracy
Building this product gives you hands-on experience in:
- RAG pipeline design — chunking, vector retrieval, prompt assembly, and citation validation
- Vector database operations — ChromaDB collections, metadata filters, and idempotent upserts
- LLM evaluation — golden set design, hit@k, MRR, and chunking config comparison
- Responsible AI patterns — PII redaction, refusal on weak evidence, and citation integrity guards
It uses Python, ChromaDB, sentence-transformers, Pydantic, and pytest.
Why this product matters: RAG, vector search, and LLM evaluation are the three skills every AI engineering role tests for. This product teaches all three in a real-world government domain with measurable pass targets.
Resources
The complete AI Powered Permit Services Assistant with RAG and Vector Search Business Requirements Document (BRD) is available as a Read-Only attachment. It provides the project specification, including the business context, objectives, scope, requirements, use cases, and implementation expectations. Review the BRD carefully before starting the implementation.
Asset Contents:
- Project overview and business objectives
- In-scope and out-of-scope definitions
- Business and technical rules, and acceptance criteria
- Key use cases and business workflows
- Core concepts — policy documents, case records, vector search, and citations
- Design and implementation requirements — CLI commands, RAG pipeline, ChromaDB, and evaluation metrics
Topics
Skills
Languages
English
Level
Intermediate
Business Domain
Government & Public Sector
Project Mentors
Labs • Projects • Practice
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