This company provides a behavioral simulation platform that uses causal models and AI-powered digital twins to predict customer choices. The platform runs causal experiments on synthetic audiences to determine the latent variables driving decisions in areas like pricing, messaging, and product design. This allows enterprises to rapidly test strategies and gain actionable insights into true behavioral drivers, replacing slow traditional market research panels.
Funding
$1M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
TBFounders
Product
Problem
Traditional market research methods are slow, expensive, and often rely on limited datasets, making it difficult for businesses to quickly and ethically understand consumer behavior and predict market impacts. Gathering sufficient data for causal inference can take months, hindering timely decision-making.
Solution
Subconscious AI offers a platform for rapid causal market research by creating digital twins of consumers using AI agents and language models. The platform allows businesses to conduct experiments and simulations on human behavior faster, more ethically, and at a lower cost than traditional methods. By leveraging a large repository of synthetic respondents, generated from data of millions of human respondents and back-tested against decades of behavioral science research, Subconscious AI enables instant user journey simulation and causal modeling. This allows companies to determine the value of product features, segment audiences by need, simulate policy outcomes, optimize patient care, and tailor content for increased engagement.
Target Audience
The primary audience includes product, marketing, and strategy teams, as well as policy makers and healthcare organizations seeking to understand and predict human behavior for informed decision-making.
Features
- Causal AI: Infers cause-and-effect relationships to enable predictions and interventions.
- Generative AI: Simulates any respondent using LLMs to design experiments with divergent thought at scale.
- Digital Twin of Society: Aggregates traits and characteristics of global citizens for reliable behavior simulation.
- Instant User Journey Simulation: Analyzes websites and competitors to pinpoint key drivers transitioning users from awareness to purchase.
- Data Augmentation: Generates synthetic consumers to enrich customer datasets for deeper market research.
- Cyclical Approach: Employs quantitative analysis, qualitative insights, and human validation for RLHF strategy.
- Accuracy/Cost Tradeoff: Delivers high accuracy at a fraction of the cost of traditional methods.