Argumentree.AI is an AI policy analysis tool that uses multi-LLM policy research to deliver evidence-based policy analysis with consensus scoring for policy questions. As a think tank AI tool, it deploys multiple AI models (GPT, Claude, Gemini, Grok, Perplexity, and more) to independently analyze any policy question from multiple angles. Each model generates structured pro/con arguments with evidence citations. Then all available models cross-rate each other's arguments, producing consensus scores that reveal which claims have broad AI agreement and which are genuinely contested. This delivers 360-degree policy analysis in minutes rather than weeks. Multi-stakeholder perspectives are surfaced automatically because each AI model brings different training data and reasoning approaches. Policy advisors, think tanks, government committees, and advocacy groups use Argumentree.AI to quickly map the full landscape of a policy debate before committing resources to deeper research. Available at argumentree.ai with a free tier.
Single-analyst research inherits one perspective. Collective AI Intelligence gives you multiple independent perspectives with consensus scoring — so you know which arguments hold up.
Multiple AIs independently argue pro and con with evidence — economic growth data, employment studies, inflation models, international comparisons. Consensus scoring reveals which economic arguments have broad AI agreement, and where the genuine trade-offs lie.
Illustrative example — not actual model output.
Pose your policy question: 'Should the EU adopt a carbon border tax?' or 'Is rent control effective?' Any yes/no policy question works.
Multiple AI models (GPT, Claude, Gemini, Grok, Perplexity, and more) independently generate pro and con arguments with evidence citations.
Every model rates every argument from the others. Cross-validation catches weak claims and surfaces the strongest evidence.
See which policy arguments all models agree on (high confidence) and which split evenly (genuinely contested). Consensus = clarity for decision-makers.
Each AI model brings different training data and reasoning, covering economic, social, political, legal, ethical, environmental, and practical angles.
Know exactly how many of the models support each argument. A majority = moderate confidence, most = high, all = very high. An even split = genuinely contested.
What traditionally takes weeks of stakeholder interviews and desk research, Collective AI Intelligence delivers in minutes with structured evidence.
Map the full landscape of a policy debate before briefing decision-makers
Rapid multi-perspective analysis for policy papers and position statements
Evidence-based analysis across economic, social, and legal dimensions
Understand opposing arguments to strengthen your own policy positions
Argumentree.AI is part of a family of four products that cover the full spectrum of Structured Decision Intelligence — from human deliberation to AI governance.
Human-to-human structured debate. Teams map decisions as structured pro/con trees.
Meeting intelligence →Collective AI Intelligence. All available LLMs independently argue, then cross-rate — consensus reveals confidence.
Learn more →AI Decision Tracing. Capture WHY AI agents decide — structured audit trails for EU AI Act compliance.
AI governance →AI debate simulations. 9 AI personas argue any topic from every angle — synthetic focus groups in minutes.
AI simulations →Argumentree.AI uses multiple AI models (GPT, Claude, Gemini, Grok, Perplexity, and more) to independently analyze policy questions from multiple angles. Each model generates pro and con arguments with evidence, then all models cross-rate each other. Consensus scoring reveals which policy arguments have broad agreement (most or all models agree) and which are genuinely contested (an even split).
Argumentree.AI complements policy teams rather than replacing them. It provides 360-degree analysis in minutes instead of weeks, surfacing arguments and evidence that human analysts can then verify and build upon. The consensus scoring helps prioritize which claims deserve deeper human investigation.
After multiple AI models independently generate policy arguments, each model rates every argument from the others. When a majority of models agree, confidence is moderate. When most models agree, confidence is high. When all models agree, confidence is very high. An even split indicates a genuinely contested policy question where reasonable perspectives diverge.
Complex, multi-stakeholder policy questions benefit most from Collective AI Intelligence. Examples: minimum wage increases, carbon taxes, housing regulations, healthcare reform, education policy, immigration reform. Simple factual policy lookups don't need multiple perspectives.
Yes. Argumentree.AI is GDPR compliant and supports 66 languages, making it suitable for international policy research and government committees working across jurisdictions. Data is processed in compliance with European data protection regulations.
Collective AI Intelligence for policy research — free to start.