Seequent, the Bentley Subsurface company, has been delivering subsurface insights to mining companies for decades now, with its solutions and industry expertise looking to empower mining companies to make well-informed decisions that enhance the processes of locating, characterising and extracting mineral resources.
Following the recent release of its 7th Geoprofessionals Data Management Report, which highlighted that mining and civil geoprofessionals turning to AI are struggling to unlock value from increasingly complex, multisource datasets, IM spoke to Dr. Janina Elliott, Seequent’s Segment Director for Mining, to find out more.
IM: According to some of Seequent’s own research there is a real industry issue in mining when it comes to data quality, cleanliness and value in the pursuit of AI-based optimisation. What is Seequent doing to help mining companies build the correct data foundations for leveraging AI? Does this even go into advising on the data collection tools?
JE: This is a very real issue, and one the industry is increasingly open about. Seequent’s own Geoprofessionals Data Management Report shows that mining specialists spend close to a third of their time on data management, yet fewer than 40% of organisations have a clearly defined data framework in place. That gap is significant, especially as interest in AI continues to grow.
From our perspective, the starting point is not AI itself, but clean data structure, traceability and accessibility. If subsurface data is fragmented, poorly validated, or locked in silos, AI simply amplifies those weaknesses rather than solving them. Seequent’s focus has therefore been on helping companies centralise geoscience data, preserve context and lineage, and make it auditable and reusable across teams and workflows.
In terms of advice, we advocate for data integration and validation capability rather than asking the industry to replacing specialist tools. Improving consistency at the point of capture ensures downstream interpretation and modelling are built on trusted inputs. The aim is to reduce the amount of rework, relogging and reinterpretation that occurs simply because data quality or provenance is unclear, which is a major hidden cost in exploration and mining today.
IM: Can you point to any recent product releases or updates that are helping with this?
JE: Several recent developments reflect this focus on data foundations. Examples here refer to continued progress in MX Deposit, our core and sample data management solution, as well as with Seequent Evo. The latter represents an open, cloud-based geoscience data and compute platform designed to bring together data from Seequent and non-Seequent applications into a single, governed environment, while maintaining openness through APIs and open data models.
At the application level, updates to tools such as Leapfrog have focused on improving data preparation, exploratory data analysis and auditability – areas that directly affect model reliability. Similarly, capabilities in products like Imago and Driver are designed to sit within established geological workflows, automating specific tasks such as core image analysis or pattern recognition, rather than acting as standalone black boxes.
A useful illustration is the recent SRK Consulting case study, where AI-assisted reinterpretation of legacy drilling data helped generate a more geologically coherent model in minutes rather than days. The key point there wasn’t speed alone, but the ability to work directly from raw, traceable data while keeping geologists firmly in control of interpretation.
IM: Where do you see Seequent’s unique selling points/market differentiators in the geoscience software space?
JE: One differentiator is longevity and focus. Seequent has spent decades specialising in subsurface understanding, building with geologists for geologists, rather than approaching mining as an extension of generic data or engineering software. That depth matters when dealing with complex geology, uncertainty and long asset lifecycles.
Another is the emphasis on visual, intuitive modelling that supports reasoning rather than replacing it. Geological interpretation is inherently uncertain and tools that allow experts to test hypotheses, iterate quickly and communicate uncertainty clearly tend to outperform rigid or overly prescriptive systems.
Finally, openness has become increasingly important. As mining organisations grow more complex and digitally mature, closed ecosystems slow innovation. Seequent’s strategy has been to support interoperability – between disciplines, vendors and stages of the mining lifecycle – so companies can evolve their digital environments incrementally rather than through disruptive system overhauls.
IM: How are you enabling your products for integration with down- and up-stream solutions across the mining space? Can you talk to any new integrations that emphasise this openness?
JE: Integration has become essential as workflows extend beyond geology into drilling, mine planning and operations. Seequent has taken an API first and standards based approach, allowing data to move between applications without forcing customers into a single vendor stack.
Recent integrations reflect this direction. For example, Evo’s existing integration with mine planning platforms such as Deswik enables smoother data flow between geological models and downstream planning. More recently, the partnership with Orica Digital Solutions, announced at PDAC in March, connects Orica’s Axis Connect drilling data with Leapfrog workflows. This helps close the loop between drill planning, execution and interpretation, reducing delays and misalignment between drilling contractors and the geoscience teams.
What’s important is that these integrations are optional and modular. Mining companies operate in highly constrained environments with legacy systems and limited tolerance for downtime. Openness allows them to modernise at their own pace, rather than through wholesale replacement.
IM: Anything else to add on the subject of geoscience software or the broader mining software space?
JE: One trend worth highlighting is that the industry is shifting away from “more activity” toward “better decisions”. Drilling more holes is expensive and increasingly ineffective as deposits become deeper and more complex. The companies that perform best are those that can build credible subsurface interpretations earlier, test scenarios quickly and reduce uncertainty before committing capital.
Technology plays a role in that shift, but it’s not about adopting the newest tool. It’s about building data foundations, enabling collaboration and supporting the geoscientist’s ability to reason, challenge assumptions, and communicate risk. In that sense, the future of mining software is about augmenting expertise in a disciplined and transparent way that allows organisations to act with agility and build proactive optimisation processes.
The post Seequent’s role in augmenting geoscience expertise appeared first on International Mining.