Unlock the secret of your data lake

By applying the right models to the right data, Itlize enables companies identify patterns in

massive volumes of data to predict and, ultimately, affect business outcomes.

Fraud detection
  • Apply predictive models to real-time transaction data to identify and stop fraudulent activity.

Customer segmentation
  • Identify customer segmentation based on behavioral, transactional, social and other data analysis.

Customer churn
  • Engineer patterns that indicate a customer is likely to leave a product or service and take steps to stop it.

Sentiment analysis
  • Analyze text-based data like email content and social media updates to glean user and customer sentiment.

Recommendation engine
  • Suggest targeted products, services and action items to users based on analysis of past behavior and other data.

Our Approach to your Business Opportunities via Data Science

Identify the Pain Point


Our data science team works with you to inspect and assess your organization's existing business segments and potential capability for big data analytics and predictive modeling. It goes beyond your technology stack to encompass your broader business organization, skills, objectives and obstacles.


Next, we work to discover data-driven business opportunities, digging out your data "ground truth" and business objectives, to identify predictive user stories, simple-to-use applications, and other data value streams.

Unlock Business Dynamics


Our data scientists explore all available data for quality, comprehensiveness and applicability to targeted user stories.


We identify data features of user stories and modeling approaches, and engineer new data features that are required for your business opportunities.

Apply Predictive Power


We evolve and refine analytic models, deploying training-vs-testing data to quantitatively measure the model's predictive performance against the right user stories.


Our data scientists work with engineers to embed the predictive power of the developed models in business logic and applications to widen engagement and drive desired outcomes.