Key Takeaways
- Causal Labs secured $6 million in seed funding, led by Kindred Ventures with participation from Refactor, BoxGroup, Factorial, Otherwise, Karman Ventures, and angel investors.
- The funding will support team expansion, further model development, and pilot programs in industries that rely on physics-based AI.
- The company is developing AI physics models to improve weather forecasting, aiming to provide faster and more accurate predictions.
- Beyond weather, Causal Labs plans to apply its models in aviation, agriculture, energy, and climate-related industries, supporting data-driven decision-making.
- Founded by AI and robotics experts Kelsie Zhao and Dar Mehta, Causal Labs is focused on building a generalized physics foundation model for large-scale applications.
Advancing AI-Powered Physics Models for Real-World Challenges
Expanding AI Capabilities Beyond Traditional Forecasting
Causal Labs, an AI company developing physics-based models for large-scale global challenges, has raised $6 million in seed funding. The round was led by Kindred Ventures with participation from Refactor, BoxGroup, Factorial, Otherwise, Karman Ventures, and angel investors.
The investment will enable Causal Labs to expand its team, improve model safety and transparency, and initiate pilot programs across industries that depend on physics-driven AI.
“We see a unique opportunity to shift the current paradigm of AI research from LLMs to physics-based models, beginning with weather—a critical and universal challenge that touches every individual, business, and community.” — Dar Mehta, Co-Founder & CEO, Causal Labs
Developing AI Models for Weather and Climate Risks
Enhancing Forecasting with AI Physics Models
Causal Labs is focused on redefining weather forecasting by using AI to simulate atmospheric behavior. Unlike traditional supercomputer-based models, which are costly and slow, the company’s approach aims to:
- Generate accurate forecasts in minutes rather than hours or days.
- Improve decision-making for industries impacted by climate variability.
- Support risk assessment and mitigation for extreme weather events.
The technology is designed to help businesses and governments make data-driven decisions, with potential applications in sectors such as disaster management, insurance, and logistics.
“Causal Labs’ AI-driven physics model research represents a major leap forward in decision-making technology in the real world.” — Steve Jang, Kindred Ventures
Beyond Weather: A General Physics Foundation Model
Expanding AI-Powered Decision-Making
Causal Labs is developing a generalized physics foundation model that extends beyond atmospheric forecasting to fields such as:
- Aviation – Optimizing flight paths and air traffic management.
- Agriculture – Enhancing climate resilience and improving resource use.
- Energy – Supporting grid reliability and renewable energy forecasting.
- Government and Space – Enabling simulations for policy planning and satellite applications.
Building a New Approach to AI
Leadership with Experience in AI and Robotics
Causal Labs was founded by Kelsie Zhao and Dar Mehta, who have backgrounds in developing AI for safety-critical applications.
- Zhao contributed to the self-driving technology stack at Cruise.
- Mehta has worked on AI research at Google, Meta, Cruise, and a YC-backed robotics startup.
The Future of AI-Driven Physics Models
Next Steps for Causal Labs
With this seed funding, Causal Labs will focus on:
- Expanding its AI and engineering team to drive research and development.
- Enhancing transparency and safety mechanisms in AI physics models.
- Launching pilot programs across industries that depend on physics simulations.
