Our data scientists have the expertise to build predictive models across all industries, both in systems old and new.
Our expertise includes building Data Models in various dimensions (Classification, Clustering, and Forecasts), industry-standard Predictive Algorithms, Data Science, and Big Data Analytics. Our team is proficient in all the leading programming languages and tools in employing the algorithms on the predictive models.
Projects we take up deliver value to your enterprise both on suggesting corrective actions based on historical data as well as proactive measures to reduce uncertainty and ensure predicted outcomes in the future.
Specific to your enterprise, the dashboards we build for the performance of your models continuously monitor the new data and serve the analytical value beyond the conventional reports.
Below are some of the typical problems we solve across verticals.
- Identification of customers who are likely to stop using a credit card and proactively engaging them with new experiences to continue.
- Target-oriented marketing campaigns for specific products and services that interest a particular segment of customers.
- Proactive customer service calls to ensure product excellence and user satisfaction.
- Predictive maintenance of the key machinery in manufacturing through real-time alerts on failures that may occur.
Our teams are ready to build models using your historical data rapidly and help you have predictable outcomes, along with analytical insights.
We define information models that capture the critical data elements in your enterprise. Often, we do this by way of examining the existing schemas, structured/unstructured data, and by interviewing the key stakeholders at various levels from different departments.
Based on the problems your company wants to solve, we categorize the models into Parametric and Non-parametric classes if we find that the established algorithms of Predictive Modeling can determine the probability of an outcome. In most other cases, we mine the transactional and historical data into Descriptive and Decision models.
Once deployed, we feed the models with the available data to study what has happened in the past and help arrive at corrective actions. The same models are then used to train with new data sets to prepare and achieve the optimal & predictable results for the future of your enterprise.
In most projects, we have a continued function after the primary deliverables in terms of monitoring the performance and fine-tuning the models (as your enterprise transforms its systems from time-to-time).