Medra
Medra is building the first Physical AI Scientist that delivers on the tight integration needed between AI that can reason, and AI that can perform experiments. Their Scientific AI can generate hypotheses, design experiments, and interpret results. Its companion system, Medra’s Physical AI, uses general-purpose robots to autonomously run experiments with the flexibility of a human and the scalability of a machine.
- Location
- San Francisco, United States, United States
- Founded
- 2020
- Category
- AI
- Funding
- VC-backed
- Team
- 11–50
Frequently asked questions
What does Medra do?
Medra is building the first Physical AI Scientist that delivers on the tight integration needed between AI that can reason, and AI that can perform experiments. Their Scientific AI can generate hypotheses, design experiments, and interpret results. Its companion system, Medra’s Physical AI, uses general-purpose robots to autonomously run experiments with the flexibility of a human and the scalability of a machine.
Where is Medra based?
Medra is based in San Francisco, United States, United States.
When was Medra founded?
Medra was founded in 2020.
How much has Medra raised?
Medra is vc-backed. Funding details have not been disclosed.
How Medra would pitch themselves
○ Auto-generated01Target customer
Companies + developers adopting AI in their stack — from indie builders to enterprise ML teams working on physical ai integrated in your lab.
02Problem they solve
Medra is building the first Physical AI Scientist that delivers on the tight integration needed between AI that can reason, and AI that can perform experiments. Their Scientific AI can generate hypotheses, design experi… The category has historically been served by tools that miss the modern workflow this product is built around.
03Key differentiator
Medra differentiates on physical ai integrated in your lab — focusing on a specific edge in this category vs. broader incumbents.
04Go-to-market strategy
Series-A scaling stage — building outbound sales motion, hiring first AEs, layering on customer success. Mix of PLG (where the product allows) + direct sales for higher-ACV deals.