MINING SOFTWARE
An IIoT, decision-making bridge
Having developed and rolled out sensing and monitoring solutions, as well as“ last-mile connectivity” products, to help reduce the capital and operation expenditure burden associated with underground mine infrastructure over the past decade-anda-bit, Maestro Digital Mine just recently strengthened its software offering with the release of Duetto Analytics.
Previously described as a bridge between IIoT devices and critical decision-making processes, Duetto Analytics is now in place at select underground mines. IM put some questions to Jacob Lachapelle, Chief Commercial Officer, to find out more.
IM: How has the launch of Duetto Analytics gone so far?
JC: Duetto Analytics has been commercially launched and is now available. It was introduced into Maestro’ s product ecosystem in September 2025 and is currently in use across underground mining environments.
Since launch, development has focused on continuous improvement informed by real operating conditions. This
Duetto Analytics works across Maestro’ s broader device ecosystem, delivering practical value at site level and remains straightforward to deploy and scale, according to the company
includes expanding functionality, refining the user experience and strengthening how Duetto works across Maestro’ s broader device ecosystem, so it delivers practical value at site level and remains straightforward to deploy and scale.
IM: Did the beta testing live up to your expectations? Are you able to share any feedback on how the solution is‘ streamlining’ maintenance?
JC: Yes, beta testing clearly lived up to our expectations. It validated that Duetto was solving the right problem and doing so in a way that aligned with how maintenance teams actually operate underground. Feedback confirmed that consolidating diagnostics, calibration status and device health into a single surface-level view improves how issues are investigated and how maintenance is planned. Just as importantly, beta testing gave us confidence that the platform performs well in real operating conditions and helped finetune how Duetto supports maintenance decision making ahead of full commercial deployment.
That validation was a key factor in moving Duetto confidently from beta into production use.
IM: Has the beta testing led to the development of any new algorithms that may go a step further in terms of aiding maintenance? Something like predicting cell degradation in a gas sensor, for instance?
JC: Duetto is already designed to provide predictive analytics and surface-level decision support for maintenance using extensive built-in diagnostics from Maestro devices. Beta testing did not change that foundation, but it helped clarify where additional intelligence delivers the most practical value for maintenance teams.
Beta discussions highlighted the realities of maintaining large sensor fleets in harsh underground environments, where temperature, humidity, calibration drift and environmental noise can all affect sensor behaviour over time. That feedback reinforced the need for analytics that interpret these factors together, rather than relying only on individual alarms or thresholds.
As a result, beta testing has helped guide development toward more contextual, diagnostic-driven intelligence, including improved differentiation between calibration-related issues, communications problems, environmental effects and early indicators of sensor degradation, with potential use of AI-assisted techniques. Predicting electrochemical cell degradation is one example that aligns with this direction, but it remains part of the ongoing development roadmap rather than a deployed capability today.
Duetto already provides the core foundation for this evolution through centralised diagnostics, calibration and maintenance records, and historical performance data. Beta feedback has ensured that future development remains grounded in real underground operating conditions and focused on delivering dependable, decision-ready insight for maintenance teams.
IM: Do you have anything else to add on the topic of mining software?
JC: One broader point worth making is that mining software is maturing. The industry is moving away from isolated point solutions and technology for its own sake, and toward software that is closely connected to physical assets, operational workflows and real decision making at site level.
What consistently matters is not the sophistication of dashboards or algorithms alone, but how effectively software helps people make safer, faster and more confident decisions in complex operating environments. That requires solutions to be grounded in high-quality data, designed around the realities of underground operations and able to integrate into existing systems rather than attempting to replace them wholesale.
There is also growing recognition that predictive and AIdriven capabilities need to be introduced responsibly. Mines want transparency, validation and control, not opaque or fully autonomous systems. The platforms that succeed will be those that build trust by supporting human expertise, simplifying complexity and delivering practical improvements over time.
From our perspective, the future of mining software lies in open, ecosystem-based platforms that connect sensors, networks, analytics and people. This approach allows mines to scale digital capability at their own pace while maintaining safety, reliability and operational confidence.
64 International Mining | FEBRUARY 2026