Problem
Users needed fast answers tied to reliable sources instead of generic model output.
Project Case Study
AWS RAG Tutor
Learning assistant that retrieves trusted context and responds with references and confidence signals.
In ProgressNext.jsAWS LambdaAPI GatewayDynamoDBOpenSearch
Goal
Deliver a retrieval-first tutoring API with source traceability and manageable cloud cost.
Architecture Overview
System shape and flow
- Ingestion pipeline chunks and indexes course material
- HTTP API routes user queries into retrieval and generation pipeline
- Response layer returns answer, cited passages, and confidence hints
Key Features
- Source citations in every response
- Configurable retrieval depth
- Feedback capture for quality tuning
Tradeoffs and Design Decisions
- Prioritized lower latency over heavy reranking
- Used managed AWS services to reduce operational burden
Challenges
- Balancing retrieval precision with answer speed
- Maintaining coherent prompts across heterogeneous documents
Results and Lessons Learned
- Better answer grounding in internal testing
- Stable API behavior under moderate concurrent load
Next Steps
- Add automated retrieval evaluation suite
- Expand ingestion connectors