Rehearsals
Deepprediction offers Rehearsals AI, a simulation platform that builds AI twins of real individuals from recorded interviews to predict human decisions with 94.1% accuracy on public benchmarks. The platform owns its foundational model (Rehearsals Engram 1.0) and first-party respondent panel, enabling marketing teams to test campaigns and product launches before committing resources.
- Artificial Intelligence
- Data & Analytics
- Marketing Technology
- AI Agents
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
Traditional market research relies on surveys and static panels that fail to capture real human decision-making complexity, leading to inaccurate predictions and slow, costly iteration. Marketing teams lack tools to simulate how actual people will respond to new products, campaigns, or messages before committing resources.
Solution
Rehearsals AI provides a simulation platform that builds AI twins of real individuals from recorded interview moments, enabling companies to predict human decisions and marketing outcomes with 94.1% accuracy against real human response distributions. Users describe their decision in plain language, and the platform guides them through narrowing the target audience and defining the desired outcome. The system spins up a background virtual machine and downloads gigabytes of simulation data to answer complex questions quickly. Every simulation draws on a vast library of validation tests comparing humans, AI twins, and real-world outcomes, returning a verifiable score with evidence. Full transparency allows users to inspect conversations, stimuli, and foundational base data behind each decision.
Target Audience
Primary customers are marketing teams, product managers, and decision-makers at companies who need to predict consumer behavior and validate campaigns, product launches, or messaging strategies before full-scale execution.
Features
- Vertically integrated platform with its own foundational model (Rehearsals Engram 1.0) and first-party respondent panel
- Conversational agent that asks clarifying questions to understand the decision, audience, and target metric
- Automated background compute that spins up a virtual machine and downloads gigabytes of simulation data per query
- Hundreds of validation tests comparing AI twins against human responses and real-world outcomes for each simulation
- End-to-end transparency with access to conversations, stimuli, and foundational base data
- Outcome recording and fine-tuning capabilities without training on customer data
- Generates a list of what-if scenarios and variable changes for follow-up Rehearsals