AT THE FOREFRONT OF DATA SCIENCE
Research and innovation are in our DNA. While continually optimizing our processes, we build proprietary technologies for data mining, machine learning, natural language, orchestration of dynamic architectures in record time, and work in the cloud.
We develop proprietary, dynamic, and self-optimizable algorithms using machine learning. The use of sophisticated features, such as Deep Learning and ensemble techniques for simultaneous testing, guarantee that our solutions require fewer and fewer interventions to turn data into precise results.
Statistical validation and data analysis
We use a variety of statistical methods to guarantee the integrity, accuracy, representativeness and credibility of information. We cross-check data to ensure consistency, conduct descriptive analysis and identify the behavior of outliers and anomalies.
A safe, failure-tolerant environment
Using advanced encryption techniques and SSL (Secure Sockets Layer), we guarantee that data transmission is safe from interception and opportunistic leaks. Besides anonymization, our solutions have distributed architecture and are able to recover from flaws in information processing extremely quickly.
Data processing and mining
We are experts in preparing data for analysis. We utilize data mining techniques to automatically identify patterns and extract relevant information from structured and unstructured data. Using a dynamic infrastructure that allows for parallel and distributed processing based on the Spark and Hadoop ecosystems.
Data engineering and storage
We build scalable database infrastructures. With NoSQL and distributed storage technology, we optimize storage and facilitate necessary operations, including the possibility of exporting this data engineering model to the native system context and to our clients’ databases.
Infrastructure configuration and monitoring are performed via software, which allows for precision and scaling flexibility in an automated and fully on-demand manner, and also offers early detection of bottlenecks. Testing, code packaging, and production deployment are also automated, minimizing human error and ensuring quality and security at delivery.