How It Works — Driving Intelligent Industrial & Chemical Engineering with AI
At Cphino, we believe the intersection of Artificial Intelligence (AI) and Chemical Engineering holds transformative potential—not just for efficiency and automation, but for safety, sustainability, and innovation across industrial and non-industrial domains. Founded by experts from IIT and DTU, Cphino leverages cutting-edge machine learning, advanced process analytics, and domain-specific engineering expertise to modernize how processes are conceptualized, controlled, and optimized.
1. Understanding the Problem Landscape
Every engineering challenge is unique — whether streamlining a chemical reactor, optimizing supply chains, or reducing energy waste. Our process begins with deep domain analysis:
- Map physical and chemical process flows
- Identify bottlenecks, inefficiencies, and safety risks
- Catalog available operational data (sensors, logs, historical performance)
Using this understanding, we define the right AI problem formulation: prediction, classification, optimization, anomaly detection, real-time control, or autonomous decision making.
2. Data Acquisition & Engineering
AI is only as good as its data. Our data pipeline includes:
- Sensor calibration and synchronization
- Data cleansing and normalization
- Time-series reconstruction
- Feature extraction and transformation
Even legacy or noisy plant data is prepared for machine learning models that handle real-world complexity.
3. Model Development & Simulation
We build models tailored to your process needs:
- Predictive models for forecasting temperatures, yields, catalyst lifetimes, and emissions
- Prescriptive models recommending optimal operating setpoints
- Reinforcement learning agents for automated control policy
- Physics-informed AI models combining domain theory with data
Frameworks used include deep learning, recurrent neural networks, graph neural networks, and hybrid first-principle models.
4. Integration into Your Operations
- Edge computing gateways for real-time inference at the plant floor
- Cloud integration for centralized analytics dashboards
- SCADA / DCS / PLC interfacing for automatic control feedback
- Human-in-the-loop dashboards for operator insights and alerts
All solutions prioritize explainability, reliability, and safety—operators retain full trust and visibility.
5. Continuous Learning & Optimization
Processes evolve, equipment ages, and operational goals change. Cphino systems support continuous improvement:
- Periodic retraining with new data
- Online learning for adaptive performance
- Automated drift detection
- Lifecycle support and updates
Your AI solution remains accurate and responsive to emerging patterns and process shifts.
Use Cases — AI in Action Across Industries
A. Chemical Manufacturing & Process Plants
- Predict Product Quality: Forecast purity or by-product levels from sensor data, enabling pre-emptive adjustments.
- Optimize Yield & Energy Efficiency: AI prescribes operating windows to reduce OPEX.
- Reduce Scrap and Rework: Detect subtle variations early to ensure consistent quality and less waste.
B. Oil & Gas Refineries
- Real-Time Anomaly Detection: Detect deviations before failures escalate.
- Predictive Maintenance Scheduling: Reduce maintenance costs and extend equipment life.
- Process Safety Enhancements: Alerts seconds before dangerous conditions.
C. Pharmaceutical & Fine Chemical Synthesis
- AI-Augmented Reaction Pathway Search: Suggest novel synthetic pathways for higher yields.
- Time-and-Resource Savings: Accelerate R&D, reduce trial-and-error.
- Scale-Up Predictability: Predict pilot and industrial scale performance.
D. Polymers & Material Manufacturing
- Inline Predictive Analytics: Forecast polymer properties during production.
- Automated Feedback Control: Adjust reactor conditions in real-time.
E. Water Treatment & Environmental Engineering
- Automated Contaminant Prediction: Predict pollutant levels for timely corrective action.
- Energy-Efficient Control: Optimize treatment stages to reduce energy consumption.
F. Non-Industrial Applications
- Food Processing Automation: Optimize cooking temperatures, moisture control, and packaging.
- Smart Agriculture Inputs: Recommend chemical inputs to maximize crop health while minimizing usage.
AI Services & Consulting — What We Offer
- Strategic AI Consulting: Assess processes and create actionable AI roadmaps.
- Customized AI Solution Development: Tailor apps for your plant, product, and goals.
- Autonomous Process Intelligence Systems: Monitor, detect deviations, adjust controls, provide insights.
- AI-Ready Data & Computing Infrastructure: Edge computing, cloud databases, IoT networks, integration layers.
- OEM Integration & Smart Plant Development: Co-develop AI modules for sensors, actuators, and predictive maintenance.
- R&D Guidance & Collaborative Projects: Design experiments, hybrid models, access curated AI toolchains, and IP collaboration.
Why Cphino?
Domain Expertise + Advanced AI + Engineering Rigor
Cphino isn’t just an AI house — we are engineers, chemists, and ML scientists delivering solutions that are:
- Impactful
- Reliable
- Explainable
- Scalable
- Aligned with business goals
Whether you’re a plant manager, R&D lead, or OEM designer, Cphino reimagines operations with intelligent automation that accelerates performance, safety, and growth.