PEnAI
PEnAI is an agentic AI solution designed to help engineering and operations teams interact with plant data, analytics, and engineering knowledge through natural language. Grounded in the IngeneroX Asset Framework, plant documents, operational data, and outputs from other IngeneroX solutions, it provides contextualized insights for monitoring, reporting, optimization, troubleshooting, asset health, and knowledge retrieval.
By bringing operational intelligence and engineering knowledge into a conversational environment, PEnAI helps teams access relevant information faster, investigate plant issues, generate reports, evaluate improvement opportunities, and retain critical engineering knowledge across the organization.
Salient Features
Client Benefits
Reduce Operational Reporting Time by 70–90%
Automate the generation of daily, weekly, and monthly operational reports, significantly reducing the engineering effort required for repetitive reporting activities.
Accelerate Root-Cause Identification
Use operational data, historical information, and engineering context to help teams identify potential root causes faster and reduce troubleshooting time.
Improve Access to Engineering Knowledge
Retrieve information from SOPs, manuals, reports, RCAs, and other technical documents through natural-language queries instead of manually searching across multiple sources.
Enable More Proactive Operations
Combine monitoring, asset health insights, early detection, and optimization intelligence to help teams identify emerging issues and improvement opportunities earlier.
Dashboard & Snapshots
![Solution configuration [Defining the Objective: Maximize Production, Minimize Utility]:](https://ingenerox.ai/wp-content/uploads/2025/05/Picture3-3.png)
![Solution configuration [Defining cases of interest – Multiple cases can also be added]:](https://ingenerox.ai/wp-content/uploads/2025/05/Picture4-3.png)
Case Studies
Development of Soft Sensor to predict the C5 contents in Debutaniser column Overhead:
Background
In modern petrochemical operations, maintaining product specifications within tight limits is critical for both quality assurance and process efficiency. One of the key challenges faced by a leading chemical plant was the need for real-time prediction and monitoring of C5 content in the overhead stream of the debutanizer column — a crucial step to ensure product specification compliance and optimize operations.
Challenge
Traditional laboratory testing methods for measuring C5 content introduced significant time delays, making real-time adjustments difficult. The plant required a fast, accurate, and reliable solution to continuously monitor C5 levels, allowing operators to take timely corrective actions and avoid off-spec products.
Solution with AnalyticX
Using AnalyticX, the engineering team was able to develop a soft sensor — a machine learning-based predictive model — specifically designed to estimate the C5 content in the debutanizer overhead stream in real time.
Key steps included:
- Seamless ingestion of historical operational data into AnalyticX without any coding requirements.
- Applying statistical analysis to identify key process variables influencing C5 concentrations.
- Rapid development and training of a machine learning model tailored to predict C5 content with high accuracy.
- Deployment of the predictive model into live operations for real-time product spec monitoring.
Results
- Enhanced Product Monitoring:
Operators now have a real-time view of the predicted C5 content, significantly reducing reliance on delayed lab measurements. - Improved Process Control:
By closely tracking C5 levels, the plant was able to make timely adjustments to operational parameters, ensuring consistent product quality. - Reduced Off-Spec Production:
Real-time insights helped minimize off-spec batches, leading to material savings and reduced reprocessing costs.
Key Takeaways
- AnalyticX enabled the rapid development of a soft sensor customized for critical KPI monitoring.
