AI-Assisted Archival Discovery Pilot

We are looking for a volunteer with experience in generative AI, retrieval-augmented generation, semantic search, vector databases, or AI application development to support a short pilot engagement. The volunteer will:
- Review the structure and readiness of our four datasets and deliver a concise dataset readiness report that highlights schema mismatches, metadata gaps, recommended preprocessing or normalization steps, and sample records suitable for indexing.
- Define a technical architecture for a public-facing pilot and deliver an architecture recommendation with rationale that compares RAG, semantic-search, and simpler approaches, identifies required components (e.g., embedding/indexing pipeline, vector store or search service, citation surface), and notes trade-offs for cost, maintainability, and transparency.
- Recommend existing platforms, tools, and services (including open-source and hosted options) that could minimize development and ongoing costs, and provide a short pros/cons list and estimated operational considerations for each recommendation.
- Build, or help us build, a small proof of concept using one of the datasets that accepts natural-language queries, returns answers grounded in the archival records, and surfaces links or citations back to the source records; deliver a working demo or deployable prototype and brief setup notes so our team can reproduce it.

Organization Mission

Nous – The New Orleans Foundation for Francophone Cultures – is a nonprofit supporting the revitalization of Louisiana's heritage cultures, focusing on Cadien (Cajun), Creole, and Indigenous communities.