Ikumi Nakamura
Founder
Unseen
Unseen offers AI-powered acoustic perception models that turn raw audio, vibration, and ultrasonic signals into real‑time, actionable insights for autonomous systems. Its pre‑trained neural networks and API‑based SDKs let developers integrate robust sound classification and event detection into robots, industrial equipment, and safety monitors without building custom signal‑processing pipelines.
- Artificial Intelligence
- Developer Tools
- Industrial Automation
- Robotics
Updated 6 months ago
Funding
Funding rounds are not available yet.
Founders
Product
Problem
Autonomous systems often struggle to interpret complex acoustic environments, where sound, vibration, and ultrasonic signals are noisy, overlapping, or difficult to process with traditional sensors, limiting reliable perception and decision‑making.
Solution
Unseen provides AI-driven acoustic perception models that convert raw audio, vibration, and ultrasonic data into actionable insights for autonomous machines. The platform offers pre‑trained neural networks that can be integrated via standard APIs, enabling robots, manufacturing equipment, and safety systems to detect, classify, and respond to acoustic events in real time. By abstracting the signal processing pipeline, Unseen allows developers to add robust acoustic understanding without building custom signal‑analysis pipelines, improving performance in noisy or dynamic environments.
Target Audience
Primary customers are developers and engineers building autonomous robots, industrial automation systems, and safety monitoring solutions that require reliable acoustic perception.
Features
- Pre‑trained deep learning models for sound, vibration, and ultrasonic signal classification
- Real‑time inference API compatible with common robotics and edge‑computing frameworks
- Noise‑robust training pipelines that handle overlapping and low‑signal‑to‑noise scenarios
- Modular SDKs for easy integration into existing control software and sensor stacks
- Continuous model updates and domain‑specific fine‑tuning options