Physics-Informed AI
Predictive Maintenance
Synthetic Data
UTokyo Engineering x Geotechnics
KIPtech - Physics x AI Engineering

Before it breaks.
Before it fails.

Our engineering team, including University of Tokyo researchers and geotechnical specialists, integrates physical models with AI to deliver predictive maintenance and slope risk assessment even when data is scarce.

No persistent sales pressure. We focus on the engineering. Built for field problems in Japan, our physics-informed AI fills gaps where failure data is limited and false alarms are too frequent.
Start with a technical consultation. We work directly on price, quality, and execution.

Tokyo, Japan - UTokyo Civil Eng. · Geotechnical AI
What We Do

Solving field problems with physics-informed AI

Synthetic anomaly data generation
01
Physics-Based Synthetic Data
We generate large volumes of anomaly data with physical models, enabling AI that could not be used because real abnormal data was too limited.
Predictive maintenance
02
Predictive Maintenance
A rare specialty in Japan
Physics-constrained time-series prediction works without abundant failure data and reduces false alarms at the root.
Slope hazard assessment
03
Slope and Sediment Hazard Assessment
Geotechnics x AI
We quantify collapse risk using pore water pressure and physical models for consultants, railways, roads, and infrastructure owners.
End-to-end delivery
04
End-to-End Delivery
Engineers directly handle discovery, requirements, implementation, and improvement proposals without unnecessary margins.
Research Evidence

Physics AI backed by research experience

Three-dimensional dynamic behaviour of embankments
Geotechnique Letters 2022 - ICE Telford Premium Prize
Three-dimensional dynamic behaviour of embankments on liquefiable ground
Source: Emerald / Institution of Civil Engineers (ICE)
Journal ->
Glacier mass balance prediction
EGUsphere Preprint 2025 - Interpretable Deep Learning
Central Asia glacier mass balance prediction with Temporal Fusion Transformer
Source: EGUsphere / Copernicus Publications
Preprint ->
Company

Company

Name
KIPtech Inc.
Address
2-2-15 Minami-Aoyama, Minato-ku, Tokyo
KIPtech
© 2026 KIPtech Inc. All rights reserved.