Plateforme de base

Autopilot IA

Name: AI Autopilot Platform
Brand: Brainiall

La couche de contrôle intelligente qui surveille, prédit et optimise en continu l'ensemble de votre exploitation en temps réel.

Brainiall AI Autopilot replaces manual tuning with continuous optimization. Traditional automation relies on static rules set by engineers who cannot monitor all interrelated variables simultaneously. Autopilot uses machine learning to map the complex, non-linear relationships between process variables and dynamically adjust setpoints — maximizing production value around the clock.

The platform sits on top of your existing control infrastructure — DCS, PLC, SCADA — reading sensor signals and writing optimized setpoints back through secure OPC connections, designed to avoid disruptions to your operators.

Designed for operations from SAG mills to flotation circuits, Autopilot delivers measurable throughput and efficiency gains across multiple commodities and processing methods. Every deployment follows the same methodology: connect, learn, optimize.

+6%Throughput gain (Brasil Mineral #441)

US$ 781KProjected annual gain (fresh ore scenario, AISC net, 2024)

25Days controlled test (Jan–Feb 2024)

AWSCloud infra via SoftwareOne partnership

Your First 30 Days

From connection to autonomous optimization — the onboarding journey.

Connect

Integrates with your existing DCS, PLC, and SCADA infrastructure. Connects without requiring new sensors or complex physical modifications. Edge connectors read data in real-time from industrial protocols.

Learn

The AI analyzes your historical and live operational data to build a multi-variable process model. It identifies hidden correlations, optimal operating windows, and constraint boundaries.

Optimize

Autopilot continuously adjusts process parameters to maximize throughput, minimize energy consumption, and prevent disruptions. Every setpoint is updated in real-time as conditions change.

Evolve

The platform continuously retrains its models with new data. As your ore body changes, equipment ages, or operating conditions shift, the AI adapts automatically to maintain peak performance.

Key Features

Enterprise-grade capabilities designed for mission-critical industrial environments.

Real-Time Monitoring

Unified dashboard with live telemetry from every sensor and actuator across your operation. Custom alerts, trend analysis, and KPI tracking at a glance.

Predictive Analytics

Forecast equipment failures, process drift, and quality deviations hours before they impact production. Catch issues before they become unplanned downtime.

Autonomous Tuning

Continuously adjusts setpoints simultaneously to keep your process at the optimal operating point. Goes far beyond what manual control or basic PID loops can achieve.

Anomaly Detection

Machine learning algorithms flag abnormal sensor readings, equipment behavior, and process deviations in real-time. Catch problems before operators notice them.

Digital Twin

A virtual replica of your operation that enables safe what-if scenario testing, operator training, and process optimization without risking real production.

Multi-Variable Optimization

Simultaneously optimizes interrelated process variables that human operators cannot manage holistically, finding higher-performing operating points across unit operations.

Applications

Flexible deployment models tailored to your operational needs.

Plant-Wide Optimization

Orchestrate all unit operations from crushing through to final product. The AI balances throughput, recovery, and energy across the entire flowsheet for maximum economic value.

Single Unit Operation

Focus on one critical bottleneck — a SAG mill, flotation bank, or leach circuit — and extract maximum performance from that single process area with targeted AI control.

Multi-Site Deployment

Deploy Autopilot across multiple mines and processing plants from a single centralized command center. Compare site performance, share learnings, and standardize best practices.

Native Integration

Autopilot connects to your existing infrastructure. We support widely-used industrial control systems, data historians, and communication protocols.

Control Systems

Siemens PCS 7ABB Ability 800xAHoneywell ExperionEmerson DeltaVRockwell PlantPAxYokogawa CENTUM

Data Historians

OSIsoft PIAVEVA HistorianGE ProficyHoneywell PHDAspenTech InfoPlus.21

Protocols

OPC UAOPC DAModbus TCPMQTTREST APIProfinet

Safety & Operator Control

Two modes. Advisory: the Autopilot recommends setpoints and the operator accepts each move. Closed loop: it sends setpoints to the control system within limits agreed with your engineers, and one click returns control to the operator. The models run in the cloud or on premises; a local agent at the plant — a Brainiall device or software on a customer server — sends the setpoints and keeps control running if the cloud connection drops. Safety instrumented systems and interlocks are never touched.

Operator Override Always Available

Human operators retain full control at all times. One click returns any parameter to manual mode. The AI assists — it never overrides human judgment.

Setpoint Constraints

Min/max boundaries configured per site and per variable. The AI optimizes within safe operating envelopes defined by your process engineers — never outside them.

Automatic Fallback on Anomaly

If the AI detects anomalous sensor readings or unexpected process behavior, it automatically reverts to manual control and alerts the operator. No intervention required.

Full Audit Trail

Every AI decision is logged with timestamp, input data, reasoning, and outcome. Complete traceability for compliance, incident review, and continuous improvement.

Verrouillages de sécurité préservés

Les systèmes instrumentés de sécurité (IEC 61511 / ISA-84) et les verrouillages restent indépendants et ne sont jamais touchés.

Deux modes, opérateur aux commandes

Deux modes de fonctionnement : recommandation (approbation de l'opérateur) et boucle fermée (consignes directes dans les limites d'ingénierie). Les déploiements respectent les zones et conduits définis par l'usine (IEC 62443-3-2).

Inside the Loop — How It Runs, Every Second

Sense → Mirror → Predict → Optimize → Act

Once live, this is the closed control loop Autopilot runs in production — continuously, every second. The plant runs in real time; the AI experiments in a digital twin and only sends a setpoint to the control system when it improves quality and throughput inside the safe envelope.

Real-time data ingest

Sense

Reads thousands of signals per second from your DCS · PLC · SCADA · historian — flow rates, pressures, vibrations, ore composition, motor current. Existing OPC UA / Modbus / MQTT / OSIsoft PI links, no new hardware.

Live process digital twin

Mirror

A live model of your process — calibrated on your historian — tracks the plant in real time. The twin is where the AI experiments. The production line is never the test bed.

Multi-variable forecast

Predict

Specialist models project how throughput, recovery, grade, and energy will evolve under current conditions — minutes ahead. Detects drift before it shows up on a control chart.

Setpoint search inside the twin

Optimize

AI searches the safe operating envelope your engineers configured — per variable, per site — for the setpoint combination that maximizes quality and throughput. Thousands of simulated scenarios run on the twin per minute. The plant feels none of them.

Setpoints, on time

Act

Sends or recommends setpoints at the right moment, in one of two modes: advisory (the operator accepts each move) or closed loop (inside limits agreed with your engineers; one click returns control to the operator). Safety instrumented systems (IEC 61511 / ISA-84) and interlocks stay independent and are never touched.

Integration

How AI Autopilot plugs into your plant

The technical integration path — 5 stages from sensor to setpoint, built on protocols your plant already runs.

01
Physical Operation
Data is gathered directly from industrial process equipment — sensors, mills, flotation cells, pumps, CCD thickeners — across the plant.
02
Supervisory System
Data flows through your existing SCADA / DCS / PLC layer via standard industrial protocols — OPC UA, Modbus, MQTT, OSIsoft PI.
03
Real-Time AI Processing
Brainiall AI Autopilot streams the data through our cloud or on-premise AI engine, applies multi-variable ML models, and computes optimal setpoints — within an operating envelope your engineers configure per variable.
04
Monitoring Dashboard
Key metrics, recommended setpoints, anomaly flags, and performance trends are displayed on the operator dashboard for visibility and override when needed.
05
Closed-Loop Feedback
Autopilot sends setpoint adjustments back to the plant in real time. The equipment operates in cruise mode; the AI keeps learning from every new data point and adapts to ore drift, equipment wear, and operational changes.

Optimized for every stage of mineral processing

AI Autopilot has models tuned for the three highest-impact operations in mining: grinding, flotation, and leaching. Each covered by its own control logic, KPIs, and ROI model.

Grinding

Real-time optimization of SAG/ball mill power, speed, feed rate, and water addition. Maintains p80 target while maximizing tons per hour across ore hardness changes. In a 25-day AI-versus-manual test at Mineração Aurizona (CMOC Group) in January–February 2024: +6% throughput (Brasil Mineral #441), with +3% in hard ore (Bond work index ≥ 14 kWh/t, above design rate). Results confirmed in writing by Mineração Aurizona in 2026.

Flotation

Continuous tuning of collector dosage, frother rate, pH, air flow, and pulp level across rougher / scavenger / cleaner circuits. AI balances recovery vs grade non-linearly, accounting for ore mineralogy. Reduces reagent consumption while holding concentrate grade within spec.

Leaching

Predictive control of reagent addition, dissolved oxygen, retention time, and CCD thickener performance. Optimizes chemical consumption and stabilizes metal recovery in leaching circuits.

Sustainability — less waste per ton produced

Every percentage point of throughput AI Autopilot delivers without a proportional increase in power, chemicals, or water is a direct reduction in environmental intensity per ton of concentrate. In the 25-day AI-versus-manual test at Mineração Aurizona (CMOC Group) in January–February 2024, specific energy consumption (kWh/t) was ~2% lower (20.7 vs 21.1 kWh/t, test report Table 1) — the additional tonnage came without burning more energy. Stable operation means less reagent over-dosing, fewer upset conditions, and tighter water-balance control — measurable gains for both bottom line and ESG reporting.

~2%Less energy per tonne (20.7 vs 21.1 kWh/t) in test report (Table 1)

↓Reagent / chemical over-dosing cut by stable operation

↓Water waste minimized via tighter pulp density control

✓Operator-in-command by design — safety interlocks untouched

Plant Assessment

A paid engagement, delivered as consulting or as the first stage of a project: under NDA, we study your process data and deliver a prioritised opportunity map and a measurement plan for a controlled AI-versus-manual test.

Book a plant assessment

Your First 30 Days

From connection to autonomous optimization — the onboarding journey.