Driving Manufacturing Efficiency: Findability Sciences’ AI Solutions in Action

CXOToday has engaged in an exclusive interview with Adarsh Jaiswal Vice President – Technology


  1. How does Findability Sciences leverage its expertise to address the specific challenges faced by manufacturing verticals? 

Findability Sciences stands at the forefront of AI Product and Solution providers, with a keen focus on facilitating traditional enterprises in harnessing the power of data and cutting-edge AI technologies. Our core expertise lies in delivering advanced Enterprise Forecasting and Business Process Co-Pilots, driven by our proprietary Findability Platform. This platform integrates AI technologies, such as Discriminative and Generative AI, within a stringent governance framework.  ‍Findability Sciences works with over 50 Global clients has established a footprint in the United States, India, Middle East, and Japan. We are committed to offering actionable AI solutions that translate into return on investment. In our approach to tackling manufacturing challenges, we utilize our extensive expertise in data analytics and AI. We employ the CUPP framework—Collection, Unification, Processing, and Presentation—to delve deep into the intricacies of manufacturing processes. By analyzing data from diverse sources, we gain valuable insights into pain points and inefficiencies within operations. Our predictive maintenance solutions are a testament to our commitment to seamless operations. By anticipating equipment failures, we effectively minimize downtime and maximize productivity. Additionally, we excel in forecasting demand and optimizing logistics to drive efficiency and reduce costs. Through the application of advanced analytics techniques such as process mining and prescriptive analytics, we uncover opportunities for process optimization and continuous improvement. Our collaborative approach with manufacturing clients ensures that our solutions are tailored to their specific needs, delivering tangible results in terms of cost savings, performance enhancements, substantial ROI, and a competitive advantage in the industry.


  1. Can you provide examples of how Findability Sciences’ solutions have improved operational efficiency within manufacturing companies? 

Select examples of the improvement are:

  • Streamlining Inventory Planning: We assisted a premier HVAC solutions provider in North America, which faced challenges with stockouts and high warehousing expenses due to a wide product range of over 6,600 products. By leveraging both machine learning and deep learning, our solution provided highly accurate inventory planning, allowing the company to optimize stock levels and warehouse space efficiently. This strategic advantage over competitors improved operational efficiency and reduced costs.

Result was increased accuracy of over 90% against current solution and cost savings in millions of dollars.

  • Price Prediction for Microelectronics Manufacturer: We aided a top-tier microelectronics manufacturer in refining SKU-level pricing strategies for trade sales. Our solution accurately predicted the best price points for each SKU, enabling the customer to maximize revenue while maintaining competitiveness in the market. This data-driven approach to pricing optimization enhanced the company’s profitability and overall performance.

Result was 98% accuracy and 92% time saving when compared to existing solution.


  1. What data-driven methodologies does Findability Sciences employ to optimize manufacturing processes and decision-making? 

At Findability Sciences, we leverage a range of data-driven methodologies to optimize manufacturing processes and decision-making. We utilize predictive analytics to forecast events such as equipment failures and demand trends. Our prescriptive analytics provides actionable recommendations for process optimization, while descriptive analytics offers insights into current performance. Process mining helps identify inefficiencies, and optimization algorithms find the most efficient solutions to complex problems. Additionally, Simulation modeling enables us to assess the impact of potential changes before implementation, ensuring informed decision-making. Through these methodologies, we empower manufacturing companies to enhance operational efficiency, reduce costs, and stay ahead of the competition. Result has been over 90% increase in accuracy and time savings when compared to current solutions.


  1. How does Findability Sciences ensure data security and compliance while working with sensitive manufacturing data? 

At Findability Sciences, we prioritize data security and compliance when managing sensitive manufacturing data. We implement robust security measures, including encryption, access controls, and data masking, to protect data both in transit and at rest. Our team undergoes regular training to stay updated on data privacy regulations and industry best practices. We also conduct thorough security audits and assessments to identify and address any vulnerabilities proactively. By adhering to stringent data governance policies and maintaining compliance with relevant regulations such as GDPR and HIPAA, we ensure that the clients’ data always remains secure and confidential. Our commitment to data security and compliance enables us to build trust with our clients and safeguard their sensitive information effectively.


  1. In what ways does Findability Sciences assist manufacturing clients in leveraging AI and machine learning for predictive maintenance and quality control? 

Our AI-driven predictive maintenance solutions use equipment (IOT) data collected from various sensors, over an extended period to anticipate potential failures, minimizing downtime and maximizing productivity. Additionally, our Image and Video solutions enable real-time quality control by inspecting products for defects or deviations from standards on the production line. By leveraging these technologies, we empower manufacturing clients to proactively maintain equipment, ensure consistent product quality, and optimize operational efficiency.


  1. Can you outline the tangible benefits that manufacturing companies have experienced through their partnership with Findability Sciences, both in terms of cost savings and performance improvements? 

Globally, the manufacturing industry is valued at trillions of dollars, with India’s manufacturing sector contributing significantly to its GDP. AI is poised to revolutionize the industry, offering immense growth opportunities. Particularly in India, where the government aims to establish the country as a global manufacturing hub, AI will play a pivotal role. With our Enterprise forecasting solutions for demand and inventory forecasting, customers have seen improvement of over 90% when compared to their existing solutions. This enabled better inventory planning and supply chain.  Additionally, Our BPC solutions have enabled users in identifying key areas which take most of their time in the important workflows of finance and procurement by 50%. This enabled major process improvement and paved the way for RPA (Robotic process Automation)

Finally, our price prediction (Enterprise forecasting) solution streamlined the Sales process of the client, enabling faster turnaround times and reducing approval times for the sales process.