Data + AI
creating smarter businesses
Improving your business intelligence
Artificial Intelligence represents the pinnacle of the digital transformation journey for companies. It elevates the potential for innovation by enabling automation in operational decision-making with unparalleled precision. This drives significant change across a wide range of industries, enhancing operational efficiency while unlocking new opportunities for products and business models.
AI has the potential to change the scenario completely, requiring a broad and strategic vision, on several levels:
Strategic plan
Implementation actions that consider team composition, interaction at all levels, employee upskilling, choice of tools, balance between short and long term and the continuous experimentation process.
Operational plan
Opportunities for efficiency gains and improvements in customer experience, associated with financial return, gains in brand perception and organizational culture.
Technology plan
Infrastructure, solution architecture, tools, processes and people for a digital transformation that promotes the use of data to increase competitiveness.
Cultural plan
Data-centric innovation and decision-making, with intense cross-functional collaboration in a common language, must be part of the DNA of organizations at the forefront of AI.
Implementation plan
Implementation actions that consider team composition, interaction at all levels, employee upskilling, choice of tools, balance between short and long term and the continuous experimentation process.
Data Science
Methods, processes and systems for extracting insights and knowledge from complex data sets, involving the application of statistics, machine learning and data analytics to understand patterns, make informed decisions and solve problems.
Data Architecture
Organized set of principles, processes and technologies that defines how data is collected, stored, processed and used in a system or organization, aiming to guarantee the integrity, security, efficiency and governance of data management, facilitating decision-making and supporting operations.
Monitoring + Maintenance
Bring more value to your customer and become attractive to users of other solutions by connecting to other tools on the market.
MLOps
Practice of integrating machine learning operations into the software development lifecycle, ensuring efficiency, consistency, and governance when deploying and managing models in production, enabling continuous and reliable delivery of machine learning-based solutions.
NLP
Natural Language Processing (NLP) focuses on the interaction between computers and human language, enabling machines to understand, interpret, and generate text in a manner similar to human communication.
Data Mesh
Data architecture to decentralize and distribute responsibility for data across the organization, by proposing that individual teams assume ownership and governance of their own data domains. This strategy aims to improve scalability, flexibility, and agility in data management in large organizations.
Data Engineering
Process of collecting, transforming and storing large volumes of data for analysis and insights, ranging from ingestion to delivery of data ready for analysis.
Machine Learning (ML)
A subset of artificial intelligence that enables systems to automatically learn and improve from past experiences without explicit programming. It relies on algorithms that analyze data, identify patterns, and make decisions, allowing computers to perform specific tasks without direct instructions.
Data Apps
Applications with a primary focus on manipulating and utilizing data, designed to efficiently collect, process, analyze, or visualize data. Data Apps can include interactive dashboards, data visualization tools, or applications specifically for data-driven insights.
Generative AI
A category of artificial intelligence that uses models to generate new and original content. These models are trained on large data sets and can then create text, images, or any other content.
Computational Vision
Development and application of algorithms and computational techniques to enable computer systems to understand and interpret visual data, replicating human capabilities and involving pattern recognition, image analysis and interpretation of visual content.
