10x Science

10x Science (YC W26) develops frontier AI models with deep memory to redefine how scientists understand and engineer biology across the life sciences, starting with drug development.

Before a drug candidate can advance to the clinic, scientists must deeply characterize the protein therapeutic to understand whether it will work. Today, that process takes months of manual, error-prone analysis. Our AI-native platform automates it, giving drug developers the confidence to advance the right candidates and stop the wrong ones early.

We are a team of three scientist-founders from Stanford, MIT, and UC Berkeley who built foundational technology in next-generation protein characterization. We are already working with multiple top-10 pharma companies and have enterprise contracts in motion. We are well-capitalized and focused on building.

Our systems are written in Rust and operate in high-throughput, natively parallelized environments across Apple Silicon and NVIDIA Blackwell GPUs. We build frontier reasoning models at the intersection of neural networks, symbolic methods, and formal methods, pushing performance through quantization, memory-time training, and custom kernel design. Our models are agentic, interpretable, and built to run at the limits of the hardware. If you enjoy working at the bare metal to make that happen, you will enjoy building with us.