ChainVision is an integrated framework for hierarchical probabilistic optimisation of mining and mineral processing operations. From iron ore to lithium. Calibrated to operator data.
Upstream decisions propagate downstream in ways that aren't modelled until they become operational problems. A mine sequence change affects ore grade. Grade affects recovery. Recovery affects concentrate quality. Concentrate quality affects refinery throughput.
Planning teams manage this complexity with disconnected tools, manual spreadsheets, and point-estimate scenarios. The result: capital decisions made without understanding the probability distribution of their downstream consequences.
Configure the chain once. Run thousands of simulated futures. Understand the full probability distribution of outcomes across every node, every product stream, every planning period.
Operations are modelled as a graph of stochastic nodes (mine, processing, refinery, logistics) with full uncertainty propagation through the chain. Outputs are probability distributions over the metrics that matter (production, grade, recovery, cost, throughput), not point estimates.
Most mining operations produce more than one product. ChainVision treats every product stream as part of the integrated value chain, with revenue distributions reflecting genuine operational uncertainty rather than deterministic averages.
Across thousands of simulated futures, ChainVision identifies which nodes constrain the chain most often. Confidence-weighted constraint analysis surfaces capital priorities that are invisible to deterministic planning.
ChainVision is designed to be calibrated against operator actuals, not run on textbook defaults. Calibration accuracy has been demonstrated against publicly available production data: Pilbara Minerals Pilgangoora ±1%, Lynas Mt Weld ±3%.
Site-level uncertainty aggregates into corporate-level views under shared stochastic drivers like commodity prices and FX. A publish-subscribe layer keeps planning views consistent across the organisation.
Each simulation produces interpretable outputs designed for planning conversations, not statistical artefacts that require translation. Probability distributions, confidence-weighted constraints, and scenario comparisons are presented in the language planners and executives already use.
Build the operation's node topology (mine, processing, refinery, logistics) and connect the streams. Set parameters from operating data or testwork, with uncertainty distributions defined per parameter rather than reduced to a single value.
ChainVision is calibrated against operator actuals where available, and runs across thousands of simulated futures. Uncertainty propagates through every node so that downstream metrics inherit the full distribution of upstream variability.
Outputs are probability distributions over production, recovery, throughput, cost, and revenue. Confidence-weighted constraints and scenario comparisons surface the decisions worth having a conversation about, at site, portfolio, and executive level.
Two named Australian mining operations, both validated against publicly available production data.
Model the probability distribution of outcomes over the full planning horizon. Understand the achievability of an annual budget before committing to it. Identify which nodes drive the most variance in production and where capital investment has the highest expected return.
Compare in-period actuals against the simulated forecast distribution as the period unfolds. Variance is interpreted in the context of the original uncertainty band, not as a deterministic miss against a single number, and the chain-wide implications of trends propagate through the same model used to set the plan.
Copula Labs is an Australian deep-technology company applying advanced stochastic methods to industrial planning problems. ChainVision is our first product.
Founded by Yazan Arouri, PhD in optimisation, with 8+ years across stochastic modelling, mathematical optimisation, and machine learning in industrial planning. Fulbright Scholar at the University of Texas at Austin. Based in Melbourne, Australia.
If you operate in Australian mining, or advise, fund, or partner with companies that do, we'd be glad to talk.