Predictive Analytics

The information extracted and verified from the native and scanned PDF documents, images and so on through izDOX AI platform becomes the input for analysis and subsequently for predictive analytics and pattern recognition for faster business decision making.

Business Need

Every organization faces unique challenges and priorities when it comes to delivering business value using AI and predictive analytics. Few of the challenges are (a) mechanism to generate required data to identify the business problems (b) collecting required data points based on the business inputs (c) having sufficient data for data analysis (d) defining the business problems (e) converting specific business problem to technical problem statements (f) technical skills required solve the problems and ensure value add to the business. The information extracted and verified from the native and scanned PDF documents, images and so on through izDOX AI platform becomes the input for analysis and subsequently for predictive analytics and pattern recognition.

Solution

bizAmica uses AI technologies like machine learning, neural networks, natural language processing to enable business process owners to combine data across different data sources and rapidly identify business problems, discover root causes, define technology problems, predict future behavior, and automate actions to continuously improve quality, utilization, and productivity of operations.

bizAmica has helped organizations around the world reduce costs by transforming business problems into business value additions. Our data scientists analyze data, predict, simulate, optimize and control check points. We provide the capabilities to mine insight from historical data and rapidly develop, test, and deploy predictive analytics, and optimization and control solutions to improve operations. Our clients are able to respond quickly to emerging market trends, gain a competitive edge over the competition and thereby grow the business.

BizAmica methodology

Methodolody_Bizamica

Summary of our methodology

  • Right strategy for right entity using predictive modeling
  • Machine, deep and transfer learning based adoptive models
  • Adoption of feedback in models to enhance prediction
  • Early prediction of behavior
  • Cost optimization

Requirements to create good ML systems

  • Problem formulation
  • Data preparation capabilities
  • Algorithms – basic and advanced
  • Actionable insights
  • Scalability

Benefits

Benefits across use-cases

1

Predict customer churn

Predict customer churn and take corrective actions to retain customers

1

Maintenance

Get notified in advanced before occurrence of any breakdown / maintenance event

1

Improve customer strategy

Identify customer behavior and improve customer centric strategy

1

Optimize cost

Optimize cost and pricing and reduce revenue leaks

1

Forecast demand

Forecast demand faster and more accurately

1

Prediction

Predict and optimize customer lifetime value (LTV) by leveraging CRM data

Are you ready for the next steps in your digital transformation journey?

    Download Case-studies