NASA · NASA-832 · record R0441

RAG Chatbots: Enhancing User and Internal Support Through Dual Knowledge Systems

National Aeronautics and Space Administration · GSFC: Goddard Space Flight Center

Overview

Development stage: In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.
High-impact designation: Not high-impactSource: c) Not high-impact
Impact justification: Not reported
Start date: Not reported
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Science
Operational functions: Chatbot or virtual assistant, Search and knowledge retrieval Derived by keyword rules; see methodology

Problem the AI is intended to solve

This work presents two complementary RAG-based chatbot systems developed for NASA's Community Coordinated Modeling Center. These tools represent practical applications of retrieval-augmented generation to enhance both external user support and internal team productivity.

Expected benefits

By implementing efficient document processing pipelines and strategic context assembly, both systems demonstrate significant response time improvements while maintaining information boundaries between public and private knowledge domains.

System outputs

The public-facing chatbot provides quick answers about CCMC tools, services, and general heliophysics information, optimized for speed and accuracy when addressing common user queries.

Technology

AI classification: Generative AISource: Generative AI: AI that generates new or synthetic content (e.g., images, videos, audio, text, code).
System name(s): Not reported
Custom-developed code: Not reported
Public source code: Not reported

Sourcing

How it was built: Not reported
Vendor (as reported): Not reported
Vendors (standardized): None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII: Not reported
Privacy Impact Assessment: Not reported
Authorization to Operate: Not reported
Demographic features: Not reported
Training and evaluation data: Not reported
Federal Data Catalog: Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Pre-deployment testingNo answer reported

AI impact assessmentNo answer reported

Independent reviewNo answer reported

Ongoing monitoringNo answer reported

Operator trainingNo answer reported

Fail-safeNo answer reported

Appeal processNo answer reported

User and public consultationNo answer reported

Potential impacts and how they were identified

Not reported