Faclon Labs Optimizes Manufacturing Processes with Intelligent Cloud Solutions

Faclon Labs is addressing the growing need for scalable, technology-driven solutions to support India’s manufacturing sector. Founded in 2016, the company specializes in AI and IoT solutions that enhance manufacturing efficiency. Its key customers include JSW, ABG, Adani, Escorts, Ultratech Cement, ITC, and Vedanta. Faclon Labs' primary offerings, I/O Sense and I/O DeepSense, support data-driven decision-making and operational optimization. I/O Sense focuses on improving utility management through robust reporting, alerting, visualization, and statistical analytics capabilities. Meanwhile, I/O DeepSense enhances decision-making through AI and ML, addressing challenges like production anomalies, cost optimization, inventory demand forecasting, equipment failure prediction, and production strategy recommendations.

In recent years, enterprises have been exploring new ways to purchase software. “In India, we’re seeing a shift from a fixed-cost model to a SaaS approach, and we wanted to explore that,” says Utkarsh Narain Srivastava, co-founder and chief technology officer at Faclon Labs. The company also needed to scale its application environment more efficiently to meet customer requirements while keeping costs under control. “Manufacturing plants operate in shifts, and our applications saw big spikes in demand when shifts began or ended,” Srivastava explains. “To accommodate that, we needed to provide dynamic scaling, which we didn’t have with our existing cloud provider.”

To provide a scalable SaaS model, Faclon Labs migrated its application environment to AWS. “We chose AWS because of its strong reputation in the cloud space and the exceptional support offered by its teams,” Srivastava recalls. The company utilized the AWS Activate program, which offers startups cloud credits, technical support, and business mentorship. “AWS Activate provided crucial support from the outset,” explains Srivastava. “We were operating on a tight budget, and the program allowed us to experiment with infrastructure that helped us with further optimization without significant upfront costs.”

Faclon Labs engaged Teleglobal International, an AWS Partner, to assist in migrating I/O Sense and I/O DeepSense to AWS. Teleglobal developed a detailed migration timeline, executed a proof of concept, and transitioned the application environment to Amazon Elastic Kubernetes Service (Amazon EKS). The partner then used AWS Application Migration Service to migrate servers including Node-RED, InfluxDB, MongoDB, Redis and other platform instances to Amazon EKS. “Teleglobal provided invaluable support by guiding us on service selection and ensuring a seamless transition to AWS,” Srivastava states.

With I/O Sense and I/O DeepSense on AWS, Faclon Labs can deliver a robust SaaS solution that easily scales to meet customer needs. “We frequently have recurring time-based computation requirements, and AWS seamlessly accommodates those,” says Srivastava. “Our applications automatically scale throughout the day without waiting for the actual load to arrive.” This capability also makes it easy for customers to add new workloads. “We no longer need to manually adjust compute capacity or infrastructure when customers onboard a new production line or plant, because Amazon EKS scales on demand,” Srivastava explains. “What used to take a couple of weeks to evaluate, and scale can now be completed in a few days.”

Faclon Labs ensures high availability and resilience for customers by utilizing Amazon EKS and AWS services, including AWS Auto Scaling. “Our customers require real-time data and insights to optimize their shop floor, and this architecture on AWS helps achieve that,” Srivastava says. The migration to Amazon EKS has also improved the performance of I/O Sense and I/O DeepSense. “We’ve observed significant performance gains, thanks to the scaling features of Amazon EKS, with response times improving by 20 to 25 percent on average and in some cases exceeding 50 percent. This allows our customers to access reports and process data views more efficiently,” explains Srivastava.

Additionally, Faclon Labs is reducing costs by following Amazon EKS architecture best practices and utilizing right-sizing capabilities. “We anticipate a 30 to 40 percent reduction in cloud costs with Amazon EKS, and we expect even greater savings as we continue fine-tuning our environment,” Srivastava says. As part of its ongoing optimization efforts, Faclon Labs is also exploring AWS AI and ML technologies. Srivastava continues, “We’re working on Vision AI solutions to enhance safety and address surface-level detection challenges. We look forward to evaluating how AWS can support these initiatives.”