TRAIL

TRAIL is KorrAI's AI workspace for risk intelligence, safety and compliance on mines and critical infrastructure such as data centers, dams, energy sites and transport corridors. It addresses a common gap: site evidence is scattered across decades of reports, instruments and imagery, and KorrAI notes that geotechnical investigation and instrumentation typically cover only about 15% of a project footprint.

TRAIL ingests documents, drawings, spreadsheets, GeoJSON/KML files and sensor feeds, and structures them into a location-anchored site ontology. AI agents reason over it and flag anomalies, gaps and contradictions. Every finding is cited to its source page or data point. Alongside the client's own data, TRAIL adds KorrAI evidence layers. The main one is a ground-deformation layer. KorrAI's UrbanSAR persistent-scatterer pipeline produces it from the public Sentinel-1 C-band archive, with commercial X-band tasking down to 0.5 m where finer detail is needed. The layer is calibrated against public and KorrAI-installed GNSS stations and corner reflectors. Other layers cover optical-imagery history (including Sentinel-2 site evolution), water and drainage, geology, natural catastrophes and site change.

Users query maps and documents in plain language and run configurable playbooks, such as piezometric, tailings water-balance or dam-deformation reviews. They keep threshold-based risk registries and draft cited reports for export to DOCX or PDF. For mine closure, TRAIL compiles submission packages against GISTM, ICMM, CDA, MAC TSM, MSHA and ANCOLD. KorrAI specialists can run screenings and deliver cited weekly or monthly reports. The platform is SOC 2 Type II and offers private VPC, on-prem or single-tenant deployment. TRAIL does not replace the Engineer of Record or field work.