Dublr
Dublr provides AI stakeholder intelligence for decision makers in diplomacy, crisis response, and public administration, grounded in validated community research. The platform simulates community responses to proposals, surfaces synthesized and cited community voices, and offers tone-matched messaging recommendations to prepare users for high-stakes negotiations.
- Data & Analytics
- Artificial Intelligence
- Government Technology
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
Leaders in diplomacy, crisis response, and public administration make high-stakes decisions without reliable insights into what specific communities care about. Traditional research is slow, expensive, and often fails to capture local context and nuance, leaving decision makers without a clear picture of community priorities before acting.
Solution
Dublr equips decision makers with AI stakeholder intelligence that is grounded in validated research, helping them understand communities at scale. The platform allows users to simulate how communities will respond to proposals before presenting them, providing tone-matched messaging and data-backed framing suggestions. It also surfaces synthesized community voices in organized, cited reports that are ready for briefing use. Dublr is built to inform decision makers—not replace them—by drawing on community understanding to deliver faster, more reliable intelligence.
Target Audience
Primary customers are leaders and decision makers in diplomacy, crisis response, and public administration who need reliable community insights to inform high-stakes negotiations and policy actions.
Features
- Scenario simulation that models community reception to specific proposals and flags potential challenges
- Community data analysis that identifies priorities (e.g., 74% of a community prioritizing visible service delivery over abstract budget figures)
- Synthesized community response analysis with receptivity scoring (e.g., 73% positive) for quick situational awareness
- Tone-matched messaging recommendations based on validated community research
- Organized, cited community intelligence ready for integration into decision-maker briefings