Edocti
Advanced Technical Training for the Software Engineer of Tomorrow
Edocti Training

AI-Driven Public Services: Automating Document Processing and Citizen Support

Intermediate
14 h
4.8 (18 reviews)

Scheduled sessions

No sessions are available at the moment.
AI-Driven Public Services: Automating Document Processing and Citizen Support

Modernizing Public IT Infrastructure: Transition from legacy, manual processes to AI-driven workflows while strictly maintaining data sovereignty and citizen privacy.

On-Premise AI Deployment: Learn how to run state-of-the-art open-source Large Language Models (like Llama 3 or Mistral) entirely within your institution's secure network, ensuring zero data leakage.

Document Automation: Combine Optical Character Recognition (OCR) with Vision-Language Models to automatically extract, categorize, and validate information from citizen applications and official forms.

Internal Virtual Assistants: Build Retrieval-Augmented Generation (RAG) systems trained on official gazettes, legal frameworks, and internal procedures to assist public servants in finding accurate answers instantly.

Who it’s for: Public Sector IT Managers, System Architects, and Technical Business Analysts responsible for modernizing government tech stacks securely.

Skills You Will Learn

On-Premise AI Deployment Data Sovereignty & Privacy OCR & LLM Data Extraction Internal RAG Systems Open-Source LLMs (Llama 3) Workflow Automation Human-in-the-Loop Design

Curriculum

Data Sovereignty and On-Premise LLMs

  • The imperative for local AI: Why public institutions must avoid external APIs for PII (Personally Identifiable Information)
  • Evaluating open-source models (Llama 3, Mistral) for government use cases
  • Deploying LLMs locally: Utilizing Ollama and vLLM for high-throughput, secure inference
  • Lab: Spinning up an air-gapped LLM environment and testing inference speeds

Automating Bureaucracy: Document Processing

  • Modern OCR pipelines: Extracting text from scanned citizen requests and handwritten forms
  • Information Extraction: Using LLMs to pull structured data (JSON) from unstructured legal or administrative documents
  • Categorization and Triage: Automatically routing citizen requests to the correct department
  • Lab: Building an automated pipeline that extracts PII from sample ID cards and application forms securely

Building Secure Internal Assistants (RAG)

  • RAG architecture for public administration: Querying the Official Gazette or internal SOPs
  • Setting up local vector databases (e.g., PostgreSQL with pgvector) for document embedding
  • Ensuring factual accuracy: Techniques to strictly ground the LLM in retrieved documents
  • Lab: Creating an internal chat assistant that answers procedural questions based exclusively on uploaded policy PDFs

System Integration and Workflow Automation

  • Connecting AI components to existing legacy public sector databases (SQL integration)
  • Event-driven architecture: Triggering AI evaluation upon form submission via citizen portals
  • Human-in-the-Loop (HITL) design: Ensuring civil servants review AI-extracted data before final approval
  • Lab: End-to-end integration mapping an automated document review workflow

Course Day Structure

  • Part 1: 09:00–10:30
  • Break: 10:30–10:45
  • Part 2: 10:45–12:15
  • Lunch break: 12:15–13:15
  • Part 3: 13:15–15:15
  • Break: 15:15–15:30
  • Part 4: 15:30–17:30

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