Limpossible®

Seeing Inside Materials. Without Touching Them.

Seeing Inside Materials. Without Touching Them.

Limpossible develops Physical AI, a platform that non-invasively characterizes the mechanical properties of materials using ultrasonic wave physics.

Physical AI that non-invasively characterizes the mechanical properties of materials using ultrasonic wave physics.

THE PROBLEM

Empirical calibration curves fail across material compositions.

Electrical monitoring cannot detect structural failure precursors before they become critical.

THE SOLUTION

Physics-Grounded AI Inference

95%

95%

Homogeneous Material Accuracy

Homogeneous Material Accuracy

90%

90%

Heterogeneous Material Accuracy

Heterogeneous Material Accuracy

3500x

3500x

Inference Speedup

Inference Speedup

One Framework. Multiple Domains.

A single physical AI framework operates across battery electrodes, soft biological tissue, and mineralized bone.
Each domain uses a physics-consistent model appropriate to its microstructure. The framework selects and applies
these models automatically based on measurement context.

A single physical AI framework operates across battery electrodes, soft biological tissue, and mineralized bone.
Each domain uses a physics-consistent model appropriate to its microstructure. The framework selects and applies these models automatically based on measurement context.

Target Applications:
1) Energy and Transportation: Structural diagnostics for battery cells, with advance warning of failure precursors that voltage and current signals cannot detect.

2) Smart Manufacturing and Infrastructure: Non-destructive evaluation of materials without disassembly.

3) Biomedical: Non-invasive tissue characterization using ultrasound with high precision.

Connect with Limpossible

s.lim@limpossible.tech

Seongjin Lim, Founder and CEO
Limpossible Inc.

Limpossible Inc. is a member of NVIDIA Inception.