Geomechanics.io

  • Free Tools
Sign UpLog In

Geomechanics.io

Geomechanics, Streamlined.

© 2026 Geomechanics.io. All rights reserved.

Geomechanics.io

CMRR-ioGEODB-ioHYDROGEO-ioQCDB-ioFree Tools & CalculatorsBlogLatest Industry News

Industries

MiningConstructionTunnelling

Company

Terms of UsePrivacy PolicyLinkedIn
    Projects
    Product

    Eclipse SourceOne EKPS expansion: workflow AI in practice for plant engineers

    June 10, 2026|

    Reviewed by Tom Sullivan

    Eclipse SourceOne EKPS expansion: workflow AI in practice for plant engineers

    First reported on International Mining – News

    30 Second Briefing

    Eclipse Data Innovations has expanded its SourceOne EKPS platform so operations teams at large industrial and mining sites can build custom, AI-powered workflow tools directly from their own time-series and event data using natural language prompts. The upgrade is aimed at tasks such as plant downtime analysis, shift handover reporting and maintenance planning, without needing bespoke coding or separate data-science projects. For engineers, this points to faster deployment of site-specific decision-support apps tightly coupled to existing historians, MES and fleet management systems.

    Technical Brief

    • Eclipse frames the upgrade as a “major expansion” of the existing EKPS architecture, not a separate product.
    • Workflow tools are intended to be “tailored to specific business challenges”, suggesting per-site configuration rather than templates.

    Our Take

    For operators already using project data environments, the move by Eclipse Data Innovations to embed AI into SourceOne EKPS suggests competitive pressure on incumbent engineering and document-control platforms to add similar, workflow-aware intelligence rather than generic analytics layers.

    Geotechnical Software for Modern Teams

    Centralise site data, logs, and lab results with GEODB-io, CMRR-io, and HYDROGEO-io.

    No credit card required.

    • Save and export unlimited calculations
    • Advanced data visualisation
    • Generate professional PDF reports
    • Cloud storage for all your projects

    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.

    Related Articles

    Hengjaya nickel mine adopts CCLAS: assay data control and grade insights for engineers
    Software
    about 16 hours ago

    Hengjaya nickel mine adopts CCLAS: assay data control and grade insights for engineers

    PT Hengjaya Mineralindo has deployed Datamine’s CCLAS laboratory information management system at its Hengjaya open-pit laterite nickel mine in Morowali, Central Sulawesi, to tighten control of saprolite and limonite assay data. The system centralises sample tracking, results validation and reporting across the nickel laboratory workflow, reducing manual data entry and the risk of transcription errors. More reliable, time-stamped laboratory data supports tighter grade control, reconciliation and ore blending decisions for the Nickel Industries Limited subsidiary.

    Future Homes carbon assessment v3: infrastructure scope explained for engineers
    Software
    8 days ago

    Future Homes carbon assessment v3: infrastructure scope explained for engineers

    Future Homes Hub has released version 3 of its Whole Life Carbon Assessment tool for new homes, aligned with the RICS Whole Life Carbon Assessment Professional Standard (2nd edition) and incorporating sector-specific defaults, assumptions and methodologies. The 2026 update extends the Conventions to cover site infrastructure, adding standard scopes for site preparation, estate roads, utilities and off-plot works that were previously a “data black hole”. For developers and civil engineers, this enables more comprehensive, comparable embodied carbon reporting across multi-site housing schemes and clearer allocation of infrastructure emissions.

    John Deere Electronics Vision Processing Unit: autonomy design notes for engineers
    Software
    12 days ago

    John Deere Electronics Vision Processing Unit: autonomy design notes for engineers

    John Deere Electronics is releasing its field-tested Vision Processing Unit (VPU) to European OEMs and machine builders, enabling integration of ruggedised, vision-based autonomy hardware into next-generation mobile machinery. The VPU is designed to run high-compute computer vision and machine learning workloads for real-time perception and decision-making, such as object detection, obstacle avoidance and path planning around mining and construction equipment. For engineers, this offers an off‑the‑shelf, validated compute platform for autonomous or operator-assist systems without developing bespoke edge hardware.

    Related Industries & Products

    Mining

    Geotechnical software solutions for mining operations including CMRR analysis, hydrogeological testing, and data management.

    CMRR-io

    Streamline coal mine roof stability assessments with our cloud-based CMRR software featuring automated calculations, multi-scenario analysis, and collaborative workflows.

    HYDROGEO-io

    Comprehensive hydrogeological testing platform for managing, analysing, and reporting on packer tests, lugeon values, and hydraulic conductivity assessments.

    GEODB-io

    Centralised geotechnical data management solution for storing, accessing, and analysing all your site investigation and material testing data.

    AllGeotechnicalInfrastructureHazardsEnvironmental