AriLinc™ goes beyond dashboards — multi-agent AI that detects process deviations, identifies root causes, and delivers corrective actions. Continuously. Autonomously.
Industrial plants are becoming increasingly complex. Growing numbers of OT devices, sensors, DCS systems, and field instruments from multiple vendors are driving operational unpredictability. AriLinc™ relieves the pressure of manual monitoring, so your engineers can focus on process improvement and efficiency — not firefighting.
Traditional quality control is reactive. Lab samples taken every 2 hours mean deviations are caught too late — after the batch is already off-spec, or wasted. AriLinc™ soft sensors predict viscosity, solid content, and purity in real time throughout the batch.
AriPrus enabled real-time operational visibility across our plants, helping us reduce downtime and improve asset utilization significantly. Their domain depth in industrial AI set them apart from every other vendor we evaluated.Discover the success story →
Most platforms stop at dashboards. AriLinc™'s Agentic AI doesn't just detect an issue — it reasons across your process data, identifies the root cause, and delivers a specific, quantified corrective action in plain language your operators can act on immediately.
Domain AI — not generic analytics. Each solution is engineered around the specific processes, failure modes, and quality parameters of your industry.
Polymerization intelligence, viscosity & solid content prediction, batch quality AI
CIP optimization, dairy quality intelligence, grains milling, inline Brix/pH monitoring
PAT-driven batch intelligence, FDA compliance, eBR automation, deviation detection
Blast furnace AI, reheating furnace optimization, rolling mill quality, energy/tonne
Turbine health monitoring, boiler efficiency, generation forecasting, carbon intelligence
Battery formation intelligence, electrode QC, OEE analytics, SAP PM automation
Flotation optimization, crusher health, ore grade prediction, conveyor reliability
Kiln intelligence, ceramics quality AI, cement clinker optimization, energy/tonne
Input your operational parameters and see projected annual savings before committing to a pilot. Typical payback: 6–12 months.
Real-time Viscosity & Solid Content % prediction in polymerization — replacing lab sampling with continuous AI-driven quality assurance.
Unified asset visibility across multiple plants — enabling predictive maintenance and reducing unplanned downtime across critical production assets.
From reactive operations to predictive decision-making — with real-time OEE dashboards and AI-driven maintenance recommendations integrated with SAP PM.
All pilots are fixed-price with defined deliverables. Scale from single-plant pilot to enterprise rollout at your pace.