Arnest
Your Partner for Progress, Performance, & Real Results
Who We Are
Arnest develops AI-powered optimization systems for process industries requiring efficiency improvements at any stage of their production lifecycle.
We specialize in process industries—cement, mining, metals, paper & pulp—where complex, non-linear operations create significant optimization opportunities.
Our approach: Production-ready AI systems that integrate with existing control infrastructure, provide explainable recommendations operators trust, and deliver measurable efficiency improvements.
We're building the next generation of industrial intelligence and seeking forward-thinking partners to validate & adopt our technology in real-world production environments.
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The Industrial Optimization Challenge
Modern industrial plants operate with increasing complexity that creates optimization opportunities:
Process Variability
Equipment behavior changes continuously with raw material quality, ambient conditions, and wear patterns—creating unpredictable operating conditions.
Multi-Variable Complexity
Adjusting one parameter (temperature, feed rate, pressure) affects dozens of others in non-linear ways. Research shows industrial processes typically involve 50-200+ interdependent variables (Source: Journal of Process Control, 2019).
Scale of Complexity
Hundreds of real-time data points from interconnected systems overwhelm manual optimization capabilities.
Cost of Inefficiency
Energy-intensive industries have 10-30% untapped efficiency potential (Source: DOE Industrial Technologies Program, 2020), meaning even minor improvements yield significant value.
Methods like manual control and static setpoints struggle to adapt quickly to these dynamic industrial conditions.
The AI Solution
AI-driven optimization provides continuous learning, real-time adaptation, and multi-variable optimization that keeps operations within optimal zones despite constant change.
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We Build Industrial AI Solutions
AI-powered Prediction & Forecasting
Anticipate future trends, optimize resource allocation, and enhance strategic planning.
Process & Performance Optimization
Streamline operations, reduce waste, and enhance overall efficiency across your industrial workflows.
Anomaly Detection & Early-Warning Systems
Proactively identify unusual patterns and prevent costly failures before they impact production.
Predictive Maintenance & Asset Intelligence
Maximize asset lifespan, minimize downtime, and ensure reliable operations with data-driven insights.
Arnest solutions seamlessly integrate with your existing DCS, PLC, SCADA, and historian systems.
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Key Equipment & Industries
Targeted Industrial Equipment
Arnest's AI solutions are specifically designed to optimize the performance and efficiency of critical industrial machinery across various sectors:
Kilns, Furnaces, & Boilers
Ball Mills, Vertical Mills, & Tube Mills
GMD System
Primary Industry Focus
Cement
Mining
Paper & Pulp
Metals
Pharma
Sugar
Rubber
Textile
Oil & Gas
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Where Our System Fits
Our solution integrates seamlessly with existing Advanced Process Control (APC) / Distributed Control System (DCS) systems and operates in real-time closed-loop control.
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Use Case: AI in Sugar Production
Arnest's AI-driven solutions optimize critical stages of sugar production, enhancing efficiency, reducing waste, and ensuring consistent product quality from cane to crystal.
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Extraction (Milling & Diffusion)
Sugar content in cane fluctuates hourly. Our TDT Engine ingests real-time process data (fiber, moisture) to simulate candidate paths and select the "Golden Path" for:
- Imbibition Water Control: Calculating the exact trajectory for water flow to maximize sugar extraction (Pol extraction) without overloading evaporators.
- Optimal Trajectory: Proactively adjusting roller speeds and pressures to prevent "choking" and maintain a stable crushing rate.
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Clarification & Evaporation (The Heat Hub)
This stage is a major source of energy waste. The TDT Engine drives stability by:
- Golden Setpoints for Vapor Bleeding: Instead of manual adjustments, the engine calculates the optimal trajectory for steam bleeding across multiple effects to ensure syrup reaches target Brix (65%–70%) with minimum steam.
- Scaling Prevention: By maintaining a stable "flight path" for temperature, the engine reduces the rate of scale formation in tubes, extending time between cleanings.
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Crystallization (Pan Boiling)
The most complex stage in sugar refining. The TDT Engine acts as an autonomous navigator:
- Precision Seeding: Calculates the optimal trajectory for vacuum and temperature to ensure uniform crystal growth.
- Eliminating "Thermal Hunting": Automating "Golden Setpoints" for pan boiling prevents "false grain" formation, significantly reducing re-melting and re-boiling.
Projected Savings with the TDT Engine
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Projected Savings: AI in Sugar Production
Arnest's TDT Engine drives a 0.5% improvement in overall efficiency, translating directly into significant financial gains by moving from reactive control to "Golden Path" navigation.
Increased Sugar Recovery
A 0.5% increase in sugar recovery (yield) translates to 500 additional tons of sugar per 1,000,000 tons of cane crushed, significantly boosting revenue.
Reduced Steam Consumption
Multi-objective optimization minimizes "thermal hunting" in evaporation and pan boiling, reducing total steam consumption and saving thousands of tons of bagasse fuel annually.
Chemical & Operational Savings
Precision pH targeting reduces lime and phosphoric acid usage by 0.5%-1.5%. Optimal Trajectory Calculation minimizes "Pol loss" in filter cake and molasses.
Annual Estimate for a Mid-Sized Sugar Mill (5,000 TCD):
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Use Case: AI in Chemical Production
Arnest's TDT Engine brings precision and efficiency to the complex processes of the chemical industry, particularly in ethanol production, ensuring high quality and reduced consumption.
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High-Precision Distillation (ENA & Ethanol)
The TDT Engine acts as an "Active Digital Twin," simulating thousands of Candidate Paths for multi-pressure distillation columns. It selects the "Golden Path" to achieve target Extra Neutral Alcohol (ENA) purity with minimal specific steam consumption (kg steam/liter). If wash quality fluctuates, the Deviation Monitoring module instantly recalculates reflux ratios and steam flow, ensuring zero quality rejects.
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Fermentation Stability
The TDT Engine calculates the optimal "flight path" for temperature and nutrient dosing throughout the 40–50 hour fermentation cycle. It proactively manages cooling water setpoints to prevent temperature spikes that could harm yeast, rigorously adhering to biological constraints.
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Boiler & Cogeneration Efficiency
For facilities relying on stable steam, the engine ingests Real-Time Process Data (bagasse moisture, fuel quality) to set the optimal Air-Fuel ratio trajectory. This Adaptive Control eliminates "thermal hunting" in boilers, providing steady steam pressure to protect turbines and ensure consistent power for chemical units.
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Effluent Treatment (Zero Liquid Discharge)
In the Multi-Effect Evaporator (MEE), the engine navigates towards the target solids concentration for spent wash. By optimizing the trajectory of steam bleeding, it reduces the energy footprint of environmental compliance by 8–12%.
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DIA—AI Value Discovery Framework
Arnest’s Data Insight Analysis (DIA) is a rapid analytics framework designed to uncover AI-driven value opportunities in existing assets and operations. It combines visual analytics and statistical methods to extract actionable insights, identify performance drivers, validate assumptions, and quantify business impact.
Prepare (Data Foundation)
- Smart data acquisition
- Automated data quality checks
- Data cleansing (null, duplicate removal)
- Noise filtering and signal enhancement
Discover (AI-Ready Insights)
- Visual analytics and trend intelligence
- Correlation and dependency mapping
- Anomaly and deviation detection
- Identification of AI leverage points
Optimize (Decision Intelligence)
- Key driver identification
- Optimal operating envelope definition
- Scenario and sensitivity analysis
- AI opportunity prioritization
Realize Value (Business Impact)
- ROI and value potential assessment
- AI use-case recommendation
- Insight-driven DIA reporting
To unlock this potential, we require your historical plant data, ideally granular data per second or minute. This enables our DIA framework to conduct a thorough analysis and provide you with a clear roadmap to ROI.
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Project Timeline
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Initiation & Planning
Project Kick-Off Meeting, Creation of Project Plan, Historical Data Collection for AI System Setup
Duration (Weeks): 2
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Hardware & OPC Connectivity Setup
Server Setup, OPC Configuration, Secure Data Pipeline Establishment
Duration (Weeks): 2
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Recommendation Module —Configuration & Fine-Tuning
Configuring the AI System to Plant Conditions, Data Integration, and Initial Parameter Fine-Tuning
Duration (Weeks): 3
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Validation Phase
Real-Time Testing of the Recommendation Module, Operator Feedback Integration, Performance Optimization & KPI Verification
Duration (Weeks): 3
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Closed Loop Module (RetroSense)—OPC Write & Fine-Tuning
Integration with Recommendation Module, Final Parameter Tuning for Optimal Control, and Write-Back Operation
Duration (Weeks): 2
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Performance Validation Phase
Closed-Loop Stability Testing, Process Efficiency Assessment, AI Utilization Ramp-Up, Final KPI Validation
Duration (Weeks): 4
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Training & Handover
Operator & Engineering Team Training, Documentation Handover, Final Acceptance
Duration (Weeks): 1
Our AI systems are proven and production-ready, requiring only configuration and validation for your specific plant conditions. Custom implementation is only needed if specific operator requirements cannot be accommodated by our standard system.
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System Technical Requirements
To ensure optimal performance and seamless integration of the Arnest RetroSense AI solution, the following technical specifications are recommended:
Hardware Specifications
- RAM: 32GB or higher
- Processor: Intel Core i9 or equivalent
- Storage: 1TB NVMe SSD
Software & Connectivity
- Operating System: Windows Server or Windows Pro
- Connectivity: OPC (Open Platform Communications)
- Network: Stable Internet connection
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RetroSense AI Solution (Kiln Optimizer)
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AI Should Amplify Human Expertise
The most effective AI doesn't replace people—it enhances their judgment, improves consistency, and elevates long-term performance.
We build systems that work alongside your teams, amplifying experience and expertise to drive measurable results.
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Our Team
Our team combines expertise in process manufacturing processes, artificial intelligence, and sustainability. We're ready to help your plant achieve new levels of efficiency and environmental performance.
Mahesh Badmanji
Co-founder & Chief Technology Officer (CTO)
Software Professional with 18 years of experience. Drives the company’s technology vision, innovation strategy, and product evolution.
Shiju Madamchery
Co-founder & VP of Engineering
Software Professional with 20 years of experience in designing scalable, enterprise-grade systems. Leads cross-functional teams to deliver scalable solutions.
Balakrishnan Athmanathan
Vice President AI
A visionary in industrial AI transformation with 18 years of experience. Leads the development of advanced, AI-powered solutions tailored to complex process industries.
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