NTWIST’s AI-driven setpoint optimization adapts in real time to process changes - boosting performance and reducing variability without added complexity.
Across real deployments
Inconsistent setpoints drain performance - and nobody has time for guesswork. Most plants still rely on static tuning or post-shift reviews. Without real-time feedback, operators chase recovery targets blind, reacting to alarms and wasting energy. Optimization never sticks.
NTWIST makes setpoint tuning continuous, adaptive, and intelligent. Our AI analyzes live circuit data to recommend optimal setpoints in real time - adjusting for ore, load, and constraint shifts. It cuts operator burden, boosts throughput, and ensures tuning is based on data, not instinct.
NTWIST replaces manual setpoint guesswork with real-time, machine learning-driven control - enabling your plant to run faster, leaner, and more predictably.
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Continuously adapts target values as conditions change - accounting for ore variability, circuit load, and system constraints.
Feeds results back into the optimization model to learn from real-world outcomes and improve recommendations over time.
Surfaces high-confidence adjustments before a process drifts off-spec - minimizing lag and reducing quality losses.
Balances throughput, recovery, energy use, and reagent consumption simultaneously - not one metric at the expense of another.
Designed to plug into existing control infrastructure (no rip-and-replace) with minimal disruption to operations.
Acts as a digital co-pilot - guiding decisions, reducing variability between shifts, and preserving expert knowledge.
NTWIST gives control room teams smarter, real-time recommendations - no more “best guesses.” Adjust fast, reduce energy use, and stabilize performance on the fly.
OSIsoft PI. SCADA. DCS. Historian. MES. ERP. WMS.
And yes — we work with whatever you’re using.
Adaptive control software that continuously recommends and refines process setpoints across grinding, flotation, and leaching circuits. Optimizes throughput, recovery, and energy efficiency using live circuit data.
Provides visibility into how process inputs and setpoints impact performance over time. Tracks variability, identifies patterns, and helps operations fine-tune control strategies with data-backed confidence.
It uses machine learning to recommend real-time process setpoints based on live plant conditions. This helps stabilize operations, improve throughput, and reduce energy usage - without rewriting your control logic.
Yes. NTWIST is system-agnostic and integrates with whatever you're already using - no rip-and-replace required.
Many sites report measurable improvements in throughput stability and energy efficiency within weeks of deployment - sometimes within the first few shifts.
Absolutely. Our models are designed to detect deviation trends and preemptively adjust setpoints before performance degrades or recovery drops.
No. Any plant looking to reduce variability, improve decision-making, and get more value from their control systems can benefit - regardless of size or maturity.
Full control. The system acts as a co-pilot - providing high-confidence recommendations while leaving operators free to accept, modify, or override them.
Not at all. It reduces noise by surfacing only what matters - real-time, actionable guidance with no need to dig through reports or dashboards.
Yes. Intelligent recommendations stay consistent regardless of who’s on the console - helping reduce variability between shifts and capturing best practices in real time.
