Mine Planning & Drilling/Blasting Design on Eigenform AI Geo Tooltips

AI-Optimized Blast Design and Execution

Mon, 21 Sep 2026 00:00:00 +0800

Key Takeaways

Strayos uses drone photogrammetry and ML/genetic-algorithm optimization trained on historical blast outcomes to recommend burden, spacing, and timing before you drill.
O-Pitblast and Deswik.Blast are established commercial alternatives with strong simulation support for the same design step.
Orica BlastIQ is the cloud platform connecting drill data through to blast execution, standardizing how design intent gets carried into the field.
Explosive loading itself (physically charging the holes) has the least AI penetration of the group — current systems mostly add QA/QC checks rather than optimization.
Fragmentation and vibration prediction from these tools is trained on your own historical blast data, so accuracy improves the more blasts you feed back into the system.

TL;DR

Feed drone-captured bench topography and your historical blast performance data into an AI blast-design platform (Strayos, O-Pitblast, or Deswik.Blast) to get an optimized pattern before drilling, then execute and track it through a connected platform like Orica BlastIQ.

Blasting Evaluation

Mon, 21 Sep 2026 00:00:00 +0800

Key Takeaways

Post-blast evaluation splits into two AI-driven tasks: tracking where the ore actually moved (Hexagon Blast Movement Intelligence) and measuring fragmentation size (Split-Desktop, WipFrag).
Hexagon BMI generates a “Muckpile Block Model” — a post-blast update to your grade-control block model — without requiring personnel to walk the muckpile to place or retrieve monitors.
Fragmentation-analysis tools use image-processing/computer-vision techniques on muckpile photos to estimate particle size distribution instead of manual sieving.
This is a genuinely mature AI application — both categories have years of field deployment behind them, not just pilot studies.

TL;DR

Evaluate blast performance with two complementary AI tools: Hexagon Blast Movement Intelligence for tracking ore movement into a muckpile block model, and image-analysis fragmentation tools like Split-Desktop or WipFrag for particle size distribution.

Blasting Sequence

Mon, 21 Sep 2026 00:00:00 +0800

Key Takeaways

Blast sequencing and timing design live inside broader blast-design suites: Orica BlastIQ and Deswik.Blast.
BlastIQ is a cloud platform for storing, managing, and sharing blast-related information, giving quality-control visibility over blast design and execution rules.
Marked “Emerging” — sequencing modules exist inside mature commercial suites, but the AI-driven optimization of sequence/timing (versus just digitizing existing manual practice) is still a developing capability.
BlastIQ has documented API integration with Deswik.Ops, so these tools aren’t necessarily either/or — they’re increasingly interoperable.

TL;DR

Manage blast sequencing and timing through cloud-based platforms like Orica BlastIQ, which centralizes blast-related data and enforces design/loading rules, with Deswik.Blast offering a comparable sequencing capability integrated into the broader Deswik suite.

Long Term Planning

Mon, 21 Sep 2026 00:00:00 +0800

Key Takeaways

Long-term mine planning is one of the more genuinely AI-native categories on this list: Maptek Evolution runs many scheduling scenarios in parallel on cloud compute, with solutions that learn from each other to iteratively improve.
Whittle (Enterprise Optimizer) and Deswik.Sched are the other major players, each with their own take on schedule optimization.
This differs from a traditional single-pass optimizer: Evolution’s approach is closer to evolutionary/genetic search than a one-shot LP solve.
Marked “Yes” (not “Emerging”) because this is a shipped, production capability, not a research prototype.

TL;DR

Run long-term mine planning through Maptek Evolution, which evaluates many scheduling scenarios in parallel and iteratively improves solutions using techniques adjacent to evolutionary search, rather than one static LP schedule.

Mining Block Model

Mon, 21 Sep 2026 00:00:00 +0800

Key Takeaways

Block modelling itself still runs on established commercial platforms: Datamine Studio RM, Maptek Vulcan, Hexagon HxGN MinePlan, and Deswik.
AI is arriving as an add-on layer, not a replacement — Datamine’s 2026 MineScape release added AI-enabled scheduling assistance built on top of existing block models.
This is marked “Emerging” deliberately: the core block-modelling engines are mature and largely non-AI; the AI value is concentrated in newer scheduling/optimization modules bolted onto them.
If you’re choosing a platform, the question isn’t “which one has AI” (most are adding it) but “how mature is the specific AI module you need.”

TL;DR

Build your mining block model in an established platform (Datamine Studio RM, Maptek Vulcan, Hexagon HxGN MinePlan, or Deswik), then look at the AI-enabled scheduling/optimization modules these vendors are now layering on top for the actual intelligence gains.

Mining Predictions Report

Mon, 21 Sep 2026 00:00:00 +0800

Key Takeaways

Production prediction reporting is consolidating into web-based platforms: Datamine Syncromine Core and Deswik.OPS.
Datamine acquired Mineware/Syncromine in 2026, signaling active consolidation in this specific niche of production scheduling and reporting.
Marked “Emerging” — these platforms consolidate reporting well, but the predictive (vs. purely descriptive/reporting) capability is still developing across the category.
If your current mining predictions report is a manually-assembled spreadsheet, moving to one of these platforms is the realistic first step before layering AI forecasting on top.

TL;DR

Consolidate daily/weekly/monthly mining production predictions into a web-based platform like Datamine Syncromine Core or Deswik.OPS rather than manually assembled spreadsheets — the reporting infrastructure is mature even though true predictive AI on top of it is still emerging.