10+ Years of Proprietary Tech.
Field-Proven Process Optimization.

Core Tech

The Age of AI:
Industrial Process Optimization Deep Tech for Analyzing and Optimizing Large-scale Processes.

Solving structural issues in existing processes that cannot be fixed by experience alone through advanced mathematical models and custom AI in a multidimensional way.

Based on extensive field experience and the latest process theories, we generate customized AI models for each individual process on a foundation of process modeling. This supports high-level decision-making for practical energy and carbon reduction, alongside ESG management.

As industrial processes grow more complex, experience and flat approaches reach their limits in optimization.

Multidimensional Process Improvement through Advanced Mathematical Modeling and Custom AI Models

Automated Data Processing + Custom AI

Discover hidden relationships between data points through AI for a deeper understanding of the process.

Enable rapid core decision-making based on scientific data.

CEPiEL Process Improvement Technology

Prediction & Management of Micro-Cumulative Losses

Identify subtle fluctuations in multiple process variables in real-time.

Predict and manage cumulative losses through AI.

Enable rational cost management by proactively addressing cumulative losses.

Solutions Reflecting Real-time Process Reality

Apply mathematical process modeling that captures even the non-linear characteristics of actual processes.

Present the optimal process modeling by comparing multiple simulation models.

Rational Costs through Modular Solutions

Modularize essential solutions such as custom AI for learning real-world data and real-time data monitoring.

Achieve maximum efficiency with minimal investment by applying only the necessary service modules to your process improvement.

Proprietary Process Improvement Models Validated by Patents and Publications

15+
Patents for Process Modeling & Process Domain AI Models

Unrivaled Technological Edge

Key Patents Selected/filed

AI-based reactor design for chemical processes
10-2733268

CFD + AI-based chemical equipment monitoring
10-2022-0115021

CFD-based reactor performance & optimization
10-2472720

ANN-based reaction-condition optimization
10-2541084

GA-based ANN construction & variable optimization
10-2546367

CVD graphene spec ML prediction model
10-2555160

PEMFC moisture control AI system
10-2837394

60+
Technical Validation Papers

Major Publications Selected

Hybrid meta-heuristic + PINN for utility optimization
JIEC, in press

Data-driven predictive maintenance for HX - integrated ML
KIChE, 2025

Optimal energy efficiency, exergy & economic analysis for H₂ refrigeration
Energy, 2025

Software platform for ANN modeling & optimization
Computers & Chem Eng, 2021

ANN-based modeling for reaction optimization
J. Cleaner Production, 2022

Unified framework: ANN + GA modeling, prediction, optimization
Chem Eng J, 2020

Technology Validated in the Field, from R&D Labs to Large-Scale Facilities

28+
Cumulative Projects

Industry-Proven Technology

From graphene synthesis prediction in chemical labs to process modeling, custom AI model construction, and process optimization for large-scale plants such as GS E&C, LG Chem, and Samsung Heavy Industries, we have successfully validated our technology. Across all projects, we achieved over 90% process prediction accuracy and reached target ranges for cost reduction and carbon footprint mitigation as defined by each project.