Operational AI for mining teams
See, decide, and act—faster with OrePulse AI
Low-latency grade intelligence
Stream grade and lithology estimates from live sensors and imagery with timestamped confidence scores—at the edge or in the cloud.
Precision geology at scale
Detect structures, contacts, and alteration zones in high detail to sharpen block models and guide dig lines and reconciliation.
Closed-loop optimization
Trigger routing, blend adjustments, and anomaly alerts via API/PLC integrations to keep throughput and recovery on target.
Simple Pricing
Flexible pricing to match any budget or team size.
Starting at
$From 249per month
14‑day pilot on Explorer & Pro. Custom POC for Enterprise. No credit card required.
Compare plans
- All plans include: multi‑layer prospectivity modeling (geology, geophysics, geochemistry, remote sensing)
- Bring your own data: drillholes, assays, grids with auto‑QC and normalization
- Explainable AI: per‑target drivers, sensitivity, and feature attributions
- GIS‑native outputs: GeoTIFF/GeoPackage export; ArcGIS & QGIS integrations
- Team collaboration: projects, versioning, comments, shareable reports
- Security by default: encryption in transit/at rest and role‑based access controls
- Explorer — $249/mo (annual) or $299/mo monthly: 2 seats, 300 modeling credits/mo (≈300 km²), 5 projects, standard basemaps & public datasets, email support
- Pro — $899/mo (annual) or $999/mo monthly: 10 seats, 2,000 credits/mo, unlimited projects, priority compute, API access, scheduled re‑runs, project‑level RBAC, priority support
- Enterprise — Custom pricing: unlimited seats, SSO/SAML, private cloud/VPC or on‑prem (air‑gapped optional), advanced RBAC & audit logs, dedicated CSM, 99.9% uptime SLA, security review & data residency options, custom model tuning
- Add‑ons: extra credits ($99 per +500), additional seats ($29/seat/mo), managed data onboarding & historical data harmonization (from $2,500)
Frequently asked questions
Turn raw geology into actionable targets
Book a 30‑minute demo. We’ll analyze a sample dataset and show how OrePulse AI prioritizes high‑value zones and improves decision speed.