Traditional R&D depends on slow, expensive physical trials that delay process stabilization. Faclon Labs builds AI-driven digital twins that model complex industrial behaviors, enabling thousands of virtual "What-if" simulations without risking shop-floor assets
Virtual modeling of products and processes using scientific and engineering principles
What-if analysis to optimize operating parameters before physical implementation
Reduced dependency on expensive plant trials for R&D and process improvement
Measurable gains in development speed, efficiency, and cost optimization
30% Faster Time to Market
Virtual prototyping and simulation accelerate the transition from R&D to stable, full-scale mass production
Improved Product & Recipe Yield
Scientific-level modeling enables the refinement of complex chemical and physical recipes for superior product quality
Reduced Monetary Losses
Eliminate the high costs associated with failed physical batches and equipment wear during experimental phases
90% Fewer Physical Trials
Run thousands of process permutations digitally to identify optimal parameters without wasting raw materials or energy
Solution Highlights
Core capabilities enabling AI-driven digital twin modeling and simulation
Co-development & Fine-tuning
Smart tools allowing customers, SMEs, and Faclon engineers to collaboratively contribute and fine-tune digital models
Agentic AI Orchestration
Advanced agent orchestration tools that leverage LLMs for complex scientific modeling and data reasoning
Ready ML Ops Infrastructure
Built-in AI tools and infrastructure to efficiently build, test, train, and deploy behavioral models at scale
Customized & Tailor-Made Design
Completely customized solutions engineered to meet specific scientific, engineering, and R&D output expectations
Data Ops & 3D Visualization
Robust data infrastructure to configure 2D and 3D visual twins mapped to real-time industrial process data
Multi-Source Data Integration
Seamlessly ingests contextual and non-contextual data from disparate industrial, legacy, and cloud resources
Why Faclon Labs
Key strengths behind scalable and production-ready digital twin deployments
Inclusive System Control
Provides complete control to your SMEs and engineers to inspect and refine models without any hidden logic
Rapid Deployment & Configuration
Focuses on configuration and fine-tuning rather than building from scratch, ensuring a faster path to results
Leveraging Open Source Models
Uses proven physical, scientific, and engineering models as a foundation for immediate, customized fine-tuning
Strong Data Science Team
Solutions are developed by a premier team of data scientists specializing in complex industrial modeling
Scalable Digital Twin Management
A robust infrastructure designed to handle and synchronize multiple digital twins across the entire enterprise
Cybersecurity Compliant
Full adherence to necessary IT security standards to ensure the safety of your process and R&D data
CASE STUDY - DIGITAL TWIN
Reducing Fuel Consumption via Digital Twins for a Pulp and Paper Leader
We implemented a high-fidelity digital twin for a 21 MW thermal power plant at one of India’s largest pulp and paper manufacturing facilities. The solution utilizes real-time "What-If" simulation to provide operators with precise recommendations for optimal operating parameters based on current fuel quality and load. By creating a virtual replica of the combustion process, the system allows the team to test adjustments in a risk-free environment, ensuring the boiler consistently operates at peak thermal efficiency
ROI < 6 Months Fuel savings achieved through virtual optimization quickly covered the total project costs
4% Coal Consumption Reduction Potential The digital twin identified optimal air-to-fuel ratios to minimize energy wastage
Improved Operations Team Productivity Engineers spent less time on trial-and-error adjustments using validated model simulations
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