One of Conjecto’s main contributions to its customers is related to the implementation and deployment of analytical models that improve the profitability of its operations, help to carry out the business strategy, and significantly increase the organization’s competitiveness. These models, built and tested using internal data automatically collected from the main management systems in the market (including ERP and CRM software platforms) constitute a set of services called Conjecto Model Services (CMS).

The efficiency of these models is the result of four essential components in intelligent decision-making processes that involve data science and, more specifically, predictive (eg, machine learning) and prescriptive (eg, optimization) analysis methods: algorithms, data, interface and innovation.

Algorithms: use of classic algorithms and new solutions implemented in advanced analytical platforms (e.g., Rulex, Carto) and features of programming languages such as R and Python; the models also make use of simulation, optimization, and frameworks that incorporate cognitive functions;

Data: historical basis of transactions and events relevant to the models; use of external public and private databases via Conjecto Data Services (CDS);

Interface: efficient use of APIs for integration with other platforms and for deployment of models in production;

Innovation: several initiatives that use state-of-the-art in advanced analytical solutions; design and implementation of new business models.