[ PUBLIC SECTOR & TOURISM ]

Secure Document Q&A

Compliance and policy archives are large, fragmented, and rarely searched well. The team that needs an answer in the next ten minutes settles for an answer in the next two days. We built a private RAG chatbot that lets staff ask plain-language questions over the archive, returns answers with source citations to the underlying PDFs, and keeps every byte inside the corporate perimeter.

Client

A national tourism authority in the GCC

Timeline

Production rollout

Role

Internal RAG chatbot delivery

Team

Pod: RAG + frontend

Year

2024

Industry

Public sector and compliance

01. The Challenge

Public-sector and regulated organisations cannot ship document content to public LLM endpoints. The default chatbot architecture violates that constraint on day one.

Search alone is not enough. Staff need answers, not just hits. Answers must show their sources or the room will not trust them.

02. The Solution

Built the retrieval layer on ChromaDB and HuggingFace embeddings, kept entirely inside the customer environment. Generation runs against Gemini Pro with retrieval-augmented prompts, and every response surfaces the source documents and page numbers it drew from.

Shipped a Next.js 16 frontend with streaming responses, a ChatGPT-style conversation surface, document upload and management, and chat history. Operations staff get a familiar interface; security teams get a deployment that respects the perimeter.