GeologicAI
AI-driven multi-sensor core scanning for critical minerals mining
For large-scale critical minerals miners needing rapid, high-fidelity core analysis, GeologicAI's integrated sensor suite and AI logging are unmatched. The enterprise-only model and hardware requirements exclude smaller explorers, but if you need sub-48-hour turnaround and consistent AI-powered logging, it's the clear leader.
- Critical minerals mining companies needing rapid core analysis
- Geologists wanting AI-assisted logging to reduce manual errors
- Large-scale mining projects requiring sub-48-hour turnaround
- Operations seeking integrated scanning, logging, and modeling workflow
- Small exploration teams with limited budgets
- Projects requiring only basic core logging without advanced sensors
- Organizations preferring piecemeal solutions from different vendors
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Skip GeologicAI if you're a small exploration team with limited budget, lack in-house geological expertise, or prefer a pay-as-you-go software-only solution.
Hardware deployment and maintenance costs are not included in any quoted service fee and can be significant for remote sites.
GeologicAI targets enterprise mining companies with custom contact-based pricing. Compared to piecemeal alternatives (e.g., separate scanner vendors + manual logging), the integrated suite can reduce overall project costs by accelerating timelines. However, smaller explorers may find cheaper options like off-the-shelf XRF analyzers or manual logging services. The $44M Series B and EDC funding suggest pricing is optimized for large-scale operations, not cost-sensitive teams.
In short
GeologicAI — AI-driven multi-sensor core scanning for critical minerals mining. Best for Critical minerals mining companies needing rapid core analysis, Geologists wanting AI-assisted logging to reduce manual errors, Large-scale mining projects requiring sub-48-hour turnaround. Contact Sales pricing.
What's new in GeologicAI
Checked 9 days agoAcross the latest 5 updates: 5 news mentions.
GeologicAI Announces Acquisition of Lumo Analytics to Complete Its Integrated Sensor Suite Across Critical Minerals and Rare Earth Elements
GeologicAI acquires Lumo Analytics, integrating LIBS-based drill core analysis to detect rare-earth and light elements, completing the only integrated sensor suite.
GeologicAI Raises $44M Series B
GeologicAI raises $44 million in Series B funding to accelerate growth and expand its decision engineering platform for critical minerals.
GeologicAI Announces Funding from EDC
GeologicAI receives funding from Export Development Canada (EDC) to support international expansion and innovation.
GeologicAI Acquires Resource Modeling Solutions
GeologicAI acquires Resource Modeling Solutions to expand its resource modeling capabilities and domain expertise.
GeologicAI Announces Strategic Partnership and Investment in Edge Copper
GeologicAI partners and invests in Edge Copper to extend high-resolution decision engineering for critical mineral exploration.
What independent users actually report about GeologicAI
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
19 mentions across 3 sources (Hacker News, YouTube, Bluesky).
- +Multi-sensor integration (RGB, XRF, hyperspectral, LiDAR, LIBS) is comprehensive.
- +AI-powered core logging claims 4x faster than manual methods.
- +Sub-48-hour turnaround time for core scanning results.
- +LIBS-based detection of REEs and light elements adds unique capability.
- +End-to-end workflow from scanning to resource modeling.
- −Virtually no community feedback or user reviews exist.
- −No verified performance data from independent sources.
- −Pricing is opaque with contact-only model.
- −May be overkill for small exploration teams.
- −Claimed 400% acceleration lacks external validation.
- • Potential consulting and training fees
- • Volume or project-based pricing
Viability Score
How likely is GeologicAI to still be operational in 12 months? Based on 4 signals — momentum (how recently it shipped), wrapper dependency, revenue model, and web presence.
Last calculated: July 2026
How we score →Key Features
- Multi-sensor core scanning: RGB, XRF, hyperspectral, LiDAR
- LIBS-based detection of REEs and light elements (via Lumo Analytics)
- AI-powered core logging on Digital Core Table
- Resource modeling with RMSP integration
- Drill Hole Optimizer for mine planning
- Sub-48-hour turnaround time
- 4x faster than manual core logging
- Over 400% project acceleration
- End-to-end workflow from scanning to modeling
- Domain expertise throughout mining cycle
- High-fidelity data capture and analytics
- Consistent logging with fewer errors
- Professional consulting and training services
- Decision engineering for critical mineral exploration
- Cloud-based digital core collaboration
About GeologicAI
GeologicAI provides an integrated multi-sensor core scanning and AI logging platform for critical minerals mining. It combines RGB, XRF, hyperspectral, LiDAR, and now LIBS (via Lumo Analytics acquisition) for the only complete integrated sensor suite, capable of detecting rare-earth elements (REEs) and light elements. The platform's Digital Core Table accelerates consistent logging 4x faster than manual methods, with sub-48-hour turnaround. The RMSP module and Drill Hole Optimizer turn core data into mine-ready resource models. GeologicAI's decision engineering approach delivers over 400% project acceleration for large-scale mining operations. Unlike piecemeal solutions, GeologicAI provides end-to-end workflow from scanning to modeling, backed by domain expertise and consulting services.
Behind the Verdict
GeologicAI stands out as the only vendor offering a fully integrated sensor suite including LIBS for REE detection. Its acquisition of Lumo Analytics and Resource Modeling Solutions, plus $44M Series B funding, signal strong momentum. The platform is purpose-built for major mining companies, delivering 4x faster logging and sub-48-hour turnaround. However, it's not for small exploration teams given the enterprise-only model and likely significant cost. Compared to piecemeal solutions providers, GeologicAI offers an end-to-end workflow from scanning to resource modeling, reducing integration headaches. Real-world caveats include hardware dependency (core scanners need to be on-site or shipped) and the need for in-house geological expertise to interpret results. We'd recommend GeologicAI for operations where data fidelity and speed directly impact drilling decisions.
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Real-world workflow fit
Concrete scenarios for the personas GeologicAI actually fits — and what changes day-one when you adopt it.
You have 10,000 meters of drill core from a new copper project and need lithological logs and assays within two weeks to support a feasibility study.
Outcome: GeologicAI scans the core with its multi-sensor rig (RGB, XRF, hyperspectral, LiDAR) within 48 hours, generates AI-based mineral logs on the Digital Core Table, and integrates the data into RMSP for resource modeling—cutting your timeline from 8 weeks to 2 weeks.
You've identified rare-earth element anomalies in soil samples and need to prioritize drill targets quickly with limited budget.
Outcome: GeologicAI's LIBS sensor (via Lumo Analytics) detects REEs and light elements in your existing core, providing rapid geochemical data. The Drill Hole Optimizer then suggests optimal locations for follow-up drilling, helping you allocate your budget to highest-potential targets.
Your team manually logs core, leading to inconsistent data and slow project advancement. You want to standardize logging across multiple sites.
Outcome: Deploying GeologicAI's Digital Core Table at each site ensures consistent logging 4x faster than manual methods, with AI flagging anomalies. Centralized cloud access lets remote experts review data in real time, reducing errors and accelerating resource modeling cycles.
Use Cases
- Accelerate core logging from weeks to hours with automated AI mineral identification.
- Integrate multi-sensor data (RGB, XRF, hyperspectral) into a unified digital core model.
- Detect rare-earth and light elements using LIBS technology for critical mineral exploration.
- Quantify geological uncertainty with advanced geostatistical modeling tools.
- Optimize drill hole placement and mine planning using real-time data and AI algorithms.
- Enable cross-team collaboration via cloud-based digital core table.
- Reduce manual logging errors and improve consistency across large drill programs.
Limitations
- GeologicAI's platform relies on specialized hardware (multi-sensor core scanners) and requires professional services for deployment and integration.
- There are no self-service or pay-as-you-go plans.
- The service is designed for enterprise mining operations and involves significant upfront investment.
as of 2026-06-28
Where the pricing makes sense
The company stage and team size where GeologicAI's pricing actually pencils out — and where peers do it cheaper.
GeologicAI targets enterprise mining companies with custom contact-based pricing. Compared to piecemeal alternatives (e.g., separate scanner vendors + manual logging), the integrated suite can reduce overall project costs by accelerating timelines. However, smaller explorers may find cheaper options like off-the-shelf XRF analyzers or manual logging services. The $44M Series B and EDC funding suggest pricing is optimized for large-scale operations, not cost-sensitive teams.
Setup time & first value
How long it actually takes to get something useful out of GeologicAI — broken out by persona, not the marketing-page minute.
For an initial pilot, expect 2-4 weeks for hardware deployment, staff training, and first batch scanning. Professional consulting services typically engage during the first month to calibrate AI models and integrate with existing workflows. Subsequent projects benefit from standardized procedures, yielding first results within 48 hours of core delivery to the scanner.
Switching to or from GeologicAI
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From manual logging workflows: GeologicAI provides on-site training and data migration support to digitize historical core logs into the Digital Core Table system.
- →From piecemeal sensor setups (e.g., separate XRF and hyperspectral): GeologicAI's integrated suite replaces multiple vendors, simplifying data pipelines and reducing reconciliation overhead.
- ↗To a different scanning service: Export digital core data in standard formats (e.g., CSV, SHP, GeoTIFF) for use with other modeling software—however, proprietary AI models may not transfer seamlessly.
- ↗To in-house processing: If leaving GeologicAI, you'll need to rebuild logging and modeling workflows from the raw sensor data, which may require significant effort.
Resources & Guides
Official links
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