Simulacra
Simulacra builds AI-powered digital twin models that replicate individual decision-making processes, enabling organizations to simulate how groups and societies will respond to policies, products, or strategic changes before implementation. The platform combines interview AI that extracts values and tacit knowledge with scalable simulations spanning consumer, economic, and urban domains. Its open-source EconSimulacra platform allows researchers to run LLM-agent-based socioeconomic simulations.
- Artificial Intelligence
- AI Agents
- Data & Analytics
- Software Only
- Enterprise Software
- Government Technology
Funding
Funding not disclosed
across 1 round
Founders
Founder details are not available yet.
Product
Problem
Decision-makers often rely on intuition or limited data when forecasting how individuals, groups, or societies will respond to policies, products, or strategic changes, leading to uncertain outcomes and costly missteps. New initiatives are typically deployed without the ability to test reactions in advance, leaving organizations exposed to unintended consequences.
Solution
Simulacra builds AI-powered digital twin models that emulate the thought processes and behaviors of individual people. By aggregating these personal twins, the platform can simulate the responses of organizations and societies to various scenarios, allowing users to test and evaluate potential decisions before implementation. The system supports end-to-end research collaborations, from problem definition and use-case design through prototype, MVP, and full-scale deployment, delivering simulation environments, analytics dashboards, and validation reports. Simulacra offers specialized digital twins for consumers, economic systems, and urban environments, each designed to model how people react to new products, policies, or events.
Target Audience
Primary customers are enterprises, government agencies, and research institutions that need data-driven decision support for policy design, market strategy, financial modeling, or organizational planning.
Features
- Interview AI that conducts dialogues to extract and structure individual values, decision patterns, and tacit knowledge for creating personal digital twins
- Consumer digital twins that reproduce purchasing and response behaviors to rapidly explore reactions to products and services
- Economic digital twins that construct virtual societies of interacting AI agents to simulate the impact of policies and institutional changes
- Urban digital twins that place LLM agents on 3D city models to simulate pedestrian flows during disasters or tourist influxes
- Open-source socioeconomic simulation platform "EconSimulacra" (MIT license, available via PyPI) for LLM-agent-based modeling
- Structured collaboration workflow covering use-case definition, PoC, KPI verification, and production rollout with deliverables including simulation platforms, evaluation dashboards, and research reports