Government & Policy

Causalis — Impact Evaluation Platform

Design, run, and report impact evaluations without specialist expertise

Launch Application

About this project

Impact evaluation traditionally requires deep methodological expertise — randomised controlled trials, difference-in-differences, regression discontinuity. Most government policy teams don't have that bandwidth in-house, so evaluations either don't happen or get outsourced expensively.

Causalis was built in collaboration with LKY School of Public Policy to compress that workflow. AI guides the user through method selection, study design, data preparation, analysis, and reporting — surfacing the right approach for the policy question without requiring the user to know the methodology by name.

Key Features

  • Four-stage workflow: agenda setting → design → analysis → reporting
  • Two-knowledge-base RAG architecture (methodology + policy domain)
  • AI guides method selection based on the policy question
  • Built with LKY School of Public Policy
  • Designed for non-specialist policy researchers

Technology

Claude with RAG, React, Node.js, Python/R, structured methodology knowledge base

Sectors

Government & PolicyPublic SectorAcademic ResearchDevelopment

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