We provide industry-specific analytical solutions which can be integrated with offerings across multiple domains. We offer solutions powered with real-time, data-driven dashboards that allow you to conquer the market challenges with greater confidence. Following an integrated approach combined with the power of Artificial Intelligence and Machine Learning algorithms, our multi-disciplinary team is committed to employing exceptional technologies for delivering digital transformation.
The concept of Full Life Cycle Analytics has been developed from our study and analysis with major companies. During the full product life-cycle from requirement congregation to product retirement, a huge amount of data is generated, structured, unstructured, distributed, or organized. With advanced analytics and Data Science in full force, enormous amount of data insights can be unlocked, which help in improving the production, development, and supply processes, and aid in becoming a customer-centric organization.
At Sailotech, the Full Life Cycle Analytics framework develops various models, identifies invisible issues, and empowers the organizations to deliver products and services flawlessly.
OEMs and manufacturers spend a considerable amount of money on warranty costs. Globalization and digital revolution have spiked smart machines to generate humongous amount of data. Advanced Analytics is used to convert yesterday’s impossible warranty challenges into today’s actionable intelligence. A robust Warranty Analytics platform helps to improve warranty forecasts, optimize production processes, improve inventory, and much more.
Emerging customer expectations, intense competition, and struggle to increase profitability are some of the major issues we see in the insurance industry today. To deal with this, the insurance companies are customizing their products and services to better fit into the demands of the customers. With the availability of data from various digital sources in complexity and volume, the insurance companies are experiencing a paradigm shift in the way they function, right from inception to completion.
The disruption arising due to increasing customer expectations, improving profits while trying to mitigate risks, reducing operational costs, and staying competitive at the same time is quite a Herculean task. Banks manage a large amount of customer data which they use for detecting fraud, marketing, and for performing simple credit risk calculations.
With margins getting smaller and demands becoming intense, manufacturing industries are undergoing transformations in order to boost their productivity and profitability. Whether it is root cause analysis or predictive maintenance, Manufacturing Analytics can provide insights to identify ineffectiveness, find possibilities for development, and avoid predicaments for every user.
Embedding connectivity and technology-resilient smart sensors to Advanced Data Analytics is transforming the traditional methods of connections to intelligent, scalable, and customizable networks. There is a huge amount of data generated from various sensors - from mobile phones, appliances, vehicles, machinery, etc. These sensors continuously monitor and report on every small piece of data to create opportunities for industries to reduce maintenance costs, predict equipment failures, create new modules, and develop intelligent solutions.
With technology advancement, organizations are embracing the new Security Analytics tools for continuous monitoring, risk management, investigations, and incident detection/response. Given the volume of security data collected every second, the collection, storage, processing, and analytics involved in every aspect has become a “Data Science” challenge by all means. But once this data is analyzed, the next step is to use this newly-discovered intelligence as a foundation for managing security strategies, tactics, and systems, much faster than before.