One of Conjecto's main contributions to its clients is related to the implementation and deployment of analytical models that improve the profitability of their operations, help execute business strategy, and significantly increase the organization's competitiveness. These models, built and tested using internal data automatically collected from the market's main management systems (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 analysis methods (e.g., machine learning) and prescriptive analysis (e.g., optimization): algorithms, data, interface, and innovation.
Algorithms: use of classic algorithms and new solutions implemented in advanced analytical platforms (e.g., Rulex, Carto) and programming language resources like R and Python; the models also make use of simulation, optimization, and frameworks that incorporate cognitive functions;
Data: historical base 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 deploying models into production;
Innovation: various initiatives that leverage the state-of-the-art in advanced analytical solutions; design and implementation of new business models.