Data Science & Predictive modelling
The dire need to promote a robust data-to-insights-to-decisions & outcomes cycle has driven organizations to leverage machine learning & AI to promote automated operations, improve decision-making, enhance customer experience, and achieve competitive lead in the market.
Working closely with organizations across industries, our data science team brings the expertise in machine learning, data engineering, data science, and customer insights to solve the most critical of our clients’ business problems.
Our Data science practitioners leverage techniques including predictive modelling, data mining, optimization, simulation to build AI/ML and analytics solutions augmenting organizations’ supply chain, customer experience, and operations. At Saksoft, data scientists champion our client’s objective of trustworthy, transparent, effective, and reliable output from ML and data science projects by embracing MLOps and Explainable AI approach.
Our Data science service spectrum extends from Data science & AI consulting, statistical programming, data pipelines, Machine learning, and Predictive analytics to Natural Language Processing, with our experienced practitioners leveraging their expertise in Azure Machine learning, Databricks MLflow and Snowflake to deploy scalable MLOps workloads and languages including R, Python and Java to fit into your technology stack.
For a Health Insurance company, we built predictive analytics model to unearth claim denial patterns and used insights to mitigate claim denials and increase claim acceptance rates. The takeaways – Faster payments, improved cashflow, and increased revenue.
When a Telecom company wanted to address delayed O2A cycle time and cut down wait times in terms of completing customer orders, we built predictive analytics models to prioritize orders, optimize resource utilization and use valuable inputs to accelerate O2A cycle time. The result was a faster O2A cycle and improvement in productivity.
A company providing secure connectivity solutions wanted to embrace proactive measures to eliminate uncertainties in device failure. We helped them leverage preventive maintenance model to reduce device downtime, maintenance costs and register increase in maintenance productivity.
Lacking an effective data-and-analytics ecosystem and wanting to improve outcomes, a public health services organization sought our advanced analytics expertise. We helped them leverage Azure ML powered predictive analytics across functions and use case cases to enhance patient care and patient experience.