CivicAI Architecture

Open-Source Small Language Models for Governance & Democracy

A scalable AI infrastructure designed for Nepal and developing countries, enabling transparent, multilingual, and sovereign civic intelligence.

System Overview

CivicAI is built as a modular ecosystem combining Small Language Models (SLMs), civic datasets, and retrieval systems to deliver accurate, explainable, and locally deployable AI for governance.

Architecture Layers

🧠 SLM Model Layer

Lightweight AI models (1B–7B parameters) optimized for governance tasks. Includes Legal, Policy, Election, and Public Service models using LoRA fine-tuning.

📚 Civic Data Layer

Structured datasets including laws, policies, elections, and public services. Designed for accuracy, transparency, and real-world civic applications.

🔍 RAG Engine

Retrieval-Augmented Generation ensures responses are grounded in real documents, reducing hallucination and improving trust.

Civic Datasets

🏛️ Governance Data

  • Constitutions & laws
  • Government regulations
  • Parliamentary records

🗳️ Election Data

  • Election results
  • Candidate profiles
  • Party manifestos

🏢 Public Services

  • Service directories
  • Procedures & documentation
  • Fees and timelines

🌐 Language Data

  • Nepali datasets
  • Multilingual corpora
  • Civic FAQs

Training Pipeline

1. Data Ingestion

Collect laws, policies, and documents

2. Processing

Clean, structure, and annotate data

3. Fine-Tuning

LoRA / QLoRA model training

4. Deployment

Cloud, local, or hybrid deployment

CivicAI APIs

POST /ask

Civic question answering

GET /laws/search

Legal search engine

GET /services

Public services directory

POST /policy/summarize

Policy explanation

Trust & Transparency

CivicAI ensures every response is grounded in real data with source citations, minimizing hallucinations and enabling accountable AI for governance systems.

Build the Future of Governance AI

Join CivicAI to create open, transparent, and local AI systems.