Ottante is a Beta 80 Group company specializing in Artificial Intelligence (AI) and Automated Machine Learning (AutoML) solutions.
We integrate the expertise of mathematicians, computer scientists, and researchers with Beta 80's proven methodologies to develop reliable and innovative solutions.
Real-world AI applications
We design flexible and scalable frameworks that enable businesses to integrate AI into their daily operations.
Scientific validation
Our solutions are tested and validated by the peer community to ensure maximum reliability. This thorough validation process not only enhances the credibility of our work but also strengthens our position at the forefront of technological progress and scientific research.
Tailored solutions
Through targeted methodologies, we accelerate the development and integration of solutions, reducing release times and maximizing return on investment for our clients.
Sustainable Meta-Modeling
In the contemporary landscape of artificial intelligence, a prevalent trend is the utilization of complex models that require significant resources. In contrast, Ottante stands out for its innovative approach: meta-modeling. Ottante focuses on compact, specialized, and sustainable machine-learning models. This enables us to deliver highly efficient models designed to adapt to an ever-evolving technological environment.
Key benefits of our solutions
Sustainable development. Sustainability is at the heart of our offerings. We create compact models by learning optimal architectures, applying customized constraints and metrics, and integrating domain knowledge. This approach enhances efficiency and makes our solutions versatile and ready for implementation in various business contexts.
Adaptability and scalability. We design sophisticated machine-learning frameworks that adapt to the evolving requirements of our clients. By leveraging advanced dynamic meta-modeling techniques, we ensure that our frameworks are not only responsive but also scalable and easily integrated into different business processes.
Human in the Loop. Our machine-learning solutions are designed to work in synergy with human experts. We offer intuitive tools, including explainability modules, anomaly detection algorithms, and large language models, which not only improve interpretability but also facilitate interaction between professionals and data, making decisions informed and timely.
Secure data management. Data protection is a top priority for us. We ensure that all data is managed securely and used to optimize the performance of our ecosystem of solutions. Our technologies allow real-time interactions with data, enabling seamless integration and the generation of meaningful results.
Ottante primarily specializes in the forecasting of dynamical systems that may be partially observable. This domain encompasses a wide array of time-varying systems, including, but not limited to, meteorological predictions, demand and consumption forecasting, and electrocardiogram classification. Through the application of advanced methodologies and analytical techniques, Ottante ensures that these models not only capture the inherent complexities of such systems but also yield valuable insights that can facilitate informed decision-making.
Additionally, Ottante operates in the field of computational control theory, which is essential in various areas, from optimal scheduling and efficient vehicle routing to strategic decision-making in trading scenarios and the determination of optimal policies in the context of the Internet of Things.
Products & Services
In addition to consultancy programs led by expert researchers, Ottante offers a range of highly versatile machine learning models and utilities. These pre-configured and pre-trained modular solutions can be easily adapted to various tasks and integrated with one another. This enables the management of heterogeneous and complex data, providing a comprehensive and customizable solution for a wide range of business needs.
6 AI & Machine Learning models
Haruspex
It is an advanced forecasting model that allows the analysis and prediction of time-varying data for univariate and multivariate time series, including structured formats such as videos. It integrates time-varying and constant heterogeneous data sources, to fully leverage the client's knowledge base. Possible application scenarios include:
Demand Forecast. Predicting the demand for resources such as electricity, raw materials in production chains, and warehouse inventory.
Multivariate Signal Forecast. Predicting each component of a complex signal made up of multiple time series, such as electrocardiographic signals, simultaneous analysis of KPIs like margins and revenues, or portfolio optimization.
Structured Signal Forecast. Predicting and analyzing video sources to identify anomalies in standardized and maintenance processes, security, anomaly detection, and analyzing group behaviors, such as emerging patterns during sports events.
WeatherMachine
It is a pre-trained, fine-tuneable model designed to deliver fast, localized, and highly accurate weather forecasting. It ensures users receive timely updates and precise predictions tailored to their specific geographic locations.
Use cases include:
Predicting solar plant output (up to +48 hours) with quarter-hour granularity to optimize positions in the energy market.
Predicting wind farm output (up to +48 hours), considering the spatial arrangement of individual turbines and potential intra- and inter-farm interactions and correlations.
Punto
It is an optimal scheduler for vehicle fleets. To date, Punto is applied in the following scenarios:
Fleet optimization. Finding the optimal fleet in terms of number and types of vehicles given a set of trips to be served, with constraints (e.g., vehicle capacity and type, schedule and tolerance, driver shift duration, loading and unloading times) and minimization objectives (e.g., number of vehicles, vehicle types, kilometers, transport times).
Fleet stress test. Simulating unexpected trips based on probabilities calculated from examples provided by the client to evaluate the fleet's capacity and the potential need for a supporting fleet.
Transport optimization. Calculating the optimal schedule to manage a set of predefined routes, with the flexibility to add unforeseen trips, account for potential delays on planned routes, and track the real-time location of each vehicle.
Zee
Plug-and-play anomaly detection module based on both signal range and pattern. Typically, this solution is applied in:
Preventive maintenance on complex machinery, where outputs from all sensors can be analyzed simultaneously, avoiding alarm flooding.
Zee is capable of detecting anomalous events from arbitrarily complex data sources, such as videos from security cameras.
Dashiboard
Thanks to an intuitive user interface, users can easily navigate through data, analyze it, and gain clear insights, feedback, and opinions. To date, Dashiboard enables:
Decision-makers to work directly with data through complex models and export real-time reports via responsive analysis flows.
Data scientists to create cutting-edge models, explore data, and build production-ready models.
End users to explore data and results using natural language.
