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Soil liquefaction alone caused $50B+ in losses in a single earthquake sequence. Until now, there was no scalable method to predict it site by site.
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Retrieve the most geotechnically similar case histories from the NGL database, with AI-generated engineering assessment.
Input your site parameters and retrieve the closest matching case histories from 8,634 real-world CPT and SPT records across 50+ earthquake events.
Compare multiple case histories on a single screen. Identify analogous site conditions to inform liquefaction probability for new assessments.
Integrate NGL data into your GIS or risk modeling workflows via REST API. Submit a JSON payload of site parameters and receive ranked matches with similarity scores and AI-generated assessment in a single response.
POST /v1/query
Authorization: Bearer <api-key>
Content-Type: application/json
{
"qc": 4.2, // Cone tip resistance (MPa)
"Ic": 1.8, // Soil behaviour type index
"FC": 18, // Fines content (%)
"depth": 6.5, // Sample depth (m)
"PGA": 0.32, // Peak ground acceleration (g)
"Mw": 6.2 // Moment magnitude
}
Our models are built on case histories from Tohoku, Christchurch, Chi-Chi, and Niigata. Not synthetic data. Every prediction traces back to physical ground truth.
Export results to your reporting workflow, query via API, or use the web interface for exploratory analysis. No proprietary lock-in.
Every prediction includes step-by-step reasoning: CSR, CRR, factor of safety. Review and sign off on the methodology, not just the number.
Major earthquake frequency is rising as urban infrastructure density grows. The exposure window is narrowing.
Seismic losses from liquefaction exceeded $50B in the 2010-2011 Canterbury earthquake sequence alone. Infrastructure is being built at planetary scale without adequate tools for ground failure prediction. GeoLiquefy changes that.
Ex-Enterprise Data Scientist, Emergent Ventures Fellow, and inventor with a proven record of AI deployment, scientific authorship, and patented geotechnical tools. Focused on transforming how ground failure is predicted and prevented.
Professor of Civil Engineering and Dean of Academics, Jaypee University of Information Technology. His work spans soil dynamics, ground improvement, and geotechnical earthquake engineering.
Professor of Civil and Environmental Engineering, Cal Poly. Works on probabilistic seismic hazard analysis, earthquake engineering, and soil liquefaction. His experience from global earthquake reconnaissance helps keep our scientific approach precise.
We offer structured pilots for geotechnical consulting firms, reinsurance analytics teams, and government infrastructure agencies. Pilots include platform access, API credentials, and direct researcher support.
