Orbyta Tech

Data Management & Architecture

We build artificial intelligence and data visualization solutions from scalable and secure data management and architecture skills designed to support complex workflows and ensure reliability and immediate and secure access to information.

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Our data management services and complex architectures

Using our expertise in data management, data analytics, and machine learning in both Amazon Web Services and Microsoft Azure environments, we develop customized artificial intelligence solutions to increase process efficiency through AI, support decision making, and monitor and enhance the security of infrastructure and buildings.

We are Microsoft Solution Partner “Modern Work.”

We design data analysis solutions to optimize business strategies and improve decision-making processes through models and algorithms that enable more effective and strategic management of information.

We implement ETL (Extraction, Transformation, Loading)procedures for data extraction and transformation.

We have a specialization in data analysis and segmentation for Online Trading and business optimization.

We apply big data and fast data management and analysis skills to the development of advanced Business Intelligence and Data Visualization solutions for monitoring business performance or environmental data.

We specialize in Machine Learning and Retrieval Augmented Generation (RAG) techniques for document automation. We can then build predictive analytics applications to support business strategies and increase the efficiency of internal processes through generative AI technologies created custom for the individual client.

We have expertise in computer vision for quality control and production support and in digital human development for customer service and onboarding.

We build scalable and secure data management platforms capable of supporting complex data streams in real time, ensuring quality, reliability and immediate access to information and reducing the risk of data loss.

We manage scalable cloud infrastructure and high-performance distributed architectures in both Microsoft Azure and Amazon Web Services environments. With experience implementing Kubernetes with custom networking and advanced monitoring tools such as OpenSearch, we ensure cloud environments optimized for resilience and observability.

Our expertise includes the development of event-driven architectures based on Docker, with the integration of technologies such as Kafka and RabbitMQ for efficient data flow management.

We also build low-latency applications for real-time telemetry to ensure fast and reliable processing in critical scenarios.

We develop solutions that can manage data from IoT devices and sensors in real time that enable monitoring of building infrastructure and transportation networks with the ultimate goal of increasing human safety and environmental sustainability.

We have particular expertise in managing connected devices via MQTT and WebSocket, and we develop applications for controlling IoT systems for Industrial Automation.

Orbyta Tech's projects

Real time data platform

The benefits of a real time data platform for rapid and secure real-time data management in the Intelligent Transport System and motorsport industry.

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AI in the service of assistive technologies

The LIS2Speech project to translate sign language in real time.

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The main technologies that Orbyta Tech works with.

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Frequently asked questions about Data Management & Architecture

Artificial intelligence (AI) is a broad field of computer science that aims to create systems capable of performing tasks that would require human intelligence, such as reasoning, language understanding, visual perception and complex problem solving. AI includes techniques such as logic, explicit rules and machine learning. Machine learning, on the other hand, is a subarea of AI that focuses on algorithms that allow computers to learn from data without being explicitly programmed for each task. In other words, machine learning is a specific technique within AI that allows systems to improve their performance through experience.

Machine learning is a subset of artificial intelligence that allows computers to learn from data without being explicitly programmed. It includes several techniques, such as supervised and unsupervised learning. Deep learning is an advanced branch of machine learning that uses deep neural networks to process large amounts of data and learn complex features. Deep neural networks are composed of many layers of artificial neurons, enabling them to tackle complex tasks such as image recognition. In summary, deep learning is a more sophisticated and powerful technique than machine learning.

Retrieval-Augmented Generation (RAG) refers to artificial intelligence models that combine information retrieval (retrieval) and text generation. They use external resources, such as documents or databases, to obtain relevant information, which is then processed to generate coherent and relevant responses. This approach improves the quality of the generated text, allowing complex questions to be answered more accurately. RAGs are used in various areas of computational linguistics, such as machine translation and machine writing.

The Internet of Things (IoT) is a concept that refers to the connection of physical objects to the Internet, enabling them to exchange data and interact with each other without the need for human intervention. These objects, such as sensors, smart home devices, vehicles and industrial equipment, are equipped with sensors and technologies that make them capable of collecting, sending and receiving information. IoT makes it possible to automate and optimize various processes, improving efficiency, safety, and user experience in various areas, such as the smart home, healthcare, logistics, and industry.