Mining Operations Turn to AI and Data Systems for Real-Time Decisions
Istanbul-based Liquid Apps is building software that combines artificial intelligence with operational data collection to help mining teams make faster, more informed decisions in the field. The company's mobile application integrates real-time data with navigation tools, allowing workers to access critical information directly at the site.
Mining operations involve multiple variables and constant uncertainty. Equipment breaks down without warning. Resource allocation decisions affect production timelines. Field personnel need current information to respond quickly. Liquid Apps addresses this by treating data not as a reporting tool but as an input for active decision-making.
Data Quality Determines AI Effectiveness
Batuhan Özdemir, founder of Liquid Apps, emphasizes that collecting data alone creates no value. The company focuses on processing raw operational data into insights that teams can act on immediately.
"Data is the most critical component for us," Özdemir said. "Collecting data is not enough on its own. The real value comes from processing that data correctly and integrating it into decision-making processes."
This distinction matters for operations professionals. An AI system trained on poor or inconsistent data produces unreliable recommendations. Structured, relevant data - gathered systematically from actual field work - is what separates working systems from failed pilots.
Where AI Works, Where It Doesn't
Liquid Apps sees clear boundaries for where AI performs well in mining. Repetitive, measurable tasks like predictive maintenance and equipment monitoring benefit from AI analysis of large datasets. The technology identifies patterns humans would miss.
Geological interpretation and other complex domains still require human expertise. Özdemir notes that these areas need more training data and domain knowledge before AI can operate independently. The most effective systems combine AI with experienced professionals who understand the specific context.
This reflects industry reality. Predictive maintenance and safety monitoring are accelerating AI adoption. Processes involving high uncertainty and interpretation still need human judgment.
From Data Collection to Operational Change
Liquid Apps emerged from Özdemir's experience as a mining engineering student at Istanbul Technical University. Early exposure to real operational challenges shaped the company's approach: start with the actual problems field teams face, then build systems around those needs.
The company is expanding beyond Istanbul, establishing operations in Bucharest to strengthen European partnerships and reach different markets.
For operations teams, the shift matters. Data becomes a central operational component rather than a compliance requirement. Better visibility and structured decision-making follow. The mining industry continues moving toward operations that are measurable, predictable, and optimized through data integration.
Learn more about AI for Operations and Data Analysis to understand how these systems apply across industries.
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