BHM GroundRisk AI

Instant, AI-driven ground-risk scoring for any property address — replacing slow, manual geotechnical desktop studies with a seconds-long assessment, scope and indicative fee.

Client

BHM Geotechnical

Industry

Engineering & Construction

AI-powered, property-level ground-risk intelligence that turns weeks of manual geotechnical desktop study into a seconds-long, address-based risk score, scope and fee.

Challenge

Property buyers, builders and developers had no fast, affordable way to gauge ground risk before committing to a site, and insurers had no quick means to triage subsidence, slope-movement or mine-related damage claims. Manual geotechnical desktop studies took days to weeks, required a specialist to manually pull geology, borehole and council overlay data from disparate sources, and priced out early-stage due diligence. BHM needed a way to give every stakeholder — from a first-home buyer to a claims adjuster — a defensible, fast risk read without diluting the professional judgement of its engineers.

Solutions

An AI risk-scoring engine (built on Anthropic Claude) that takes a single property address and returns a risk score, recommended scope of investigation and an indicative fee in seconds.
Live integration with NSW MinView/GSNSW, Geoscience Australia and council DCP/LEP planning overlays so every score is grounded in authoritative geology, mining and planning data.
Six role-based dashboards — Property Buyer, Builder/Developer, Insurer/Loss Adjuster, BHM Engineer, BHM Sales and System Admin — each surfacing only the workflows and data relevant to that user.
An AI claim-triage workflow for insurers that classifies likely damage cause (reactive clay, slope movement, mine subsidence, etc.) to speed up loss-adjuster decisions.
An engineer review-and-approval queue so no AI-drafted report, scope or fee is released to a client without professional sign-off.
Role-based access control (RBAC) and a configurable risk model and pricing engine, managed centrally by System Admins.

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Impact

Ground-risk assessment time cut from an estimated 2–3 weeks of manual desktop study to under 60 seconds for an address-based AI score — roughly a 95%+ reduction.
Faster insurance claim triage, with AI pre-classifying likely damage cause at 64–91% confidence before a loss adjuster ever opens the file.
BHM engineers review a queue of AI-drafted scopes (4+ pending at a time) rather than manually researching each site from scratch, reclaiming an estimated 60% of research time per job.
A single unified platform now serves all 6 user roles — buyers, developers, insurers, engineers, sales and admin — replacing fragmented spreadsheets and one-off reports.

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Challenge

Solutions

An AI risk-scoring engine (built on Anthropic Claude) that takes a single property address and returns a risk score, recommended scope of investigation and an indicative fee in seconds.
Live integration with NSW MinView/GSNSW, Geoscience Australia and council DCP/LEP planning overlays so every score is grounded in authoritative geology, mining and planning data.
Six role-based dashboards — Property Buyer, Builder/Developer, Insurer/Loss Adjuster, BHM Engineer, BHM Sales and System Admin — each surfacing only the workflows and data relevant to that user.
An AI claim-triage workflow for insurers that classifies likely damage cause (reactive clay, slope movement, mine subsidence, etc.) to speed up loss-adjuster decisions.
An engineer review-and-approval queue so no AI-drafted report, scope or fee is released to a client without professional sign-off.
Role-based access control (RBAC) and a configurable risk model and pricing engine, managed centrally by System Admins.

Impact

Ground-risk assessment time cut from an estimated 2–3 weeks of manual desktop study to under 60 seconds for an address-based AI score — roughly a 95%+ reduction.
Faster insurance claim triage, with AI pre-classifying likely damage cause at 64–91% confidence before a loss adjuster ever opens the file.
BHM engineers review a queue of AI-drafted scopes (4+ pending at a time) rather than manually researching each site from scratch, reclaiming an estimated 60% of research time per job.
A single unified platform now serves all 6 user roles — buyers, developers, insurers, engineers, sales and admin — replacing fragmented spreadsheets and one-off reports.