Tulpa builds AI agents that combine generative and reinforcement‑learning techniques with behavioural science to capture expert knowledge and explain the reasoning behind their actions. By providing causal, “why‑based” insights, the platform enables high‑stakes, time‑critical decision‑making where humans can interpret, control, and trust machine recommendations. It is designed for organizations that need to preserve and augment the expertise of their most experienced employees.
Funding
Funding not disclosed
Founders
Product
Problem
Organizations handling high‑stakes, time‑critical decisions often rely on expert knowledge that is tacit, difficult to codify, and vulnerable to loss or inconsistency. Traditional generative AI and reinforcement‑learning agents provide recommendations but lack transparency, making it hard for users to trust or verify actions in safety‑critical workflows.
Solution
Tulpa offers a platform that creates AI agents by combining generative models, reinforcement learning, and behavioural‑science methods to capture expert decision logic. The agents generate recommendations together with explicit explanations of the reasoning, causal insights, and “what‑if” analyses. By presenting the underlying rationale, users can interpret, validate, and control the AI’s actions, enabling trusted human‑machine teaming for complex, high‑pressure tasks. The system continuously encodes and updates expert knowledge, allowing organizations to preserve and scale their most valuable expertise.
Target Audience
Primary customers are enterprises and agencies operating in high‑risk domains such as cybersecurity, critical infrastructure, defense, and complex industrial operations that require expert decision support and transparent AI assistance.
Features
- Integrated pipeline that captures expert decision processes and encodes them into AI models using behavioural‑science techniques
- Generative and reinforcement‑learning agents that produce actionable recommendations with step‑by‑step explanations
- Causal AI layer that surfaces “why” and “what‑if” scenarios, enabling users to explore alternative outcomes
- Real‑time interpretability dashboard that visualizes reasoning paths and risk factors for each suggested action
- Secure, enterprise‑grade deployment that supports high‑trust human‑machine interaction in time‑critical environments