GeologicAI–Lumo Analytics LIBS acquisition: workflow gains for mine planners
Reviewed by Joe Ashwell
First reported on International Mining – News
30 Second Briefing
GeologicAI has acquired Lumo Analytics, adding what it calls the most compact and efficient Laser-Induced Breakdown Spectroscopy (LIBS) scanner on the market to its High-Resolution Decision Engineering platform for critical minerals. The LIBS unit uses high‑energy laser pulses to vaporise a tiny volume of material and read elemental composition in near real time, without destroying the core or chip sample. Integrating LIBS with GeologicAI’s existing sensor suite should tighten ore characterisation workflows, particularly for rapid geometallurgical logging and grade control in core sheds and on drill sites.
Technical Brief
- Acquisition gives GeologicAI full ownership of Lumo’s compact LIBS hardware and associated analytics IP.
- Lumo’s scanner form factor is designed to fit directly into mobile drill‑site logging units.
- Integration targets continuous, conveyor‑style scanning of core and chips rather than point‑and‑shoot assays.
- LIBS data streams are intended to be fused with existing hyperspectral and X‑ray sensors in a single platform.
- Workflow focus is rapid geometallurgical domaining and ore–waste discrimination directly in core sheds.
- Near‑real‑time outputs are aimed at shortening feedback loops between drilling, modelling and short‑term planning.
- For brownfield operations, the combined suite is positioned as a retrofit to existing core logging lines.
Our Take
Within our 357 Mining stories, only a small subset of the 586 keyword-matched pieces on AI and artificial intelligence deal with full hardware–software integration for core logging, so GeologicAI’s move positions it among the more vertically integrated digital geology players rather than just another software vendor.
Because this deal is framed around critical minerals rather than bulk commodities, it aligns with other coverage where AI-driven sensing is being deployed to tighten geological models in complex, multi-element orebodies, which can materially affect cut-off decisions and resource classification.
For project teams, an integrated sensor suite from a single supplier like GeologicAI can simplify QA/QC and data governance compared with mixing tools from multiple vendors, but it also increases dependence on that vendor’s calibration standards and long-term support model.
Prepared by collating external sources, AI-assisted tools, and Geomechanics.io’s proprietary mining database, then reviewed for technical accuracy & edited by our geotechnical team.
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