Make IT Simple



The software relies on an advanced IoT infrastructure analysing in real-time the status the components.


The software uses a combination of innovative Machine Learning techniques to predict the likelihood of failure of the observed component.


Exploiting the most advanced prescriptive techniques and considering the analysis of the predicitions and the data of the current and future production, the software computes the optimal production and maintenance plan.

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Research and Consultancy

Research and Development

The MindIT team for more than a decade is involved in the design and development of software systems to support decisions based on predictive and prescriptive techniques. The products and services offered by MindIT exploit the modularity and configurability of Synapse, a proprietary framework used to integrate machine learning, data analytics and optimization.

Synapse Framework

Analysis and Consultancy

We can model, design and develop advanced and data-driven decision support software systems. The innovative integration between machine learning and optimization techniques allows MindIT developers to design efficient, robust and intuitive products.

It's not about ideas. It's about making ideas happen.

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The MindIT team can rely on a strategic know-how in Mathematical and Constraint Optimization, both in deterministic and stochastic environment. These techniques can be employed to develop scalable and efficient solutions for optimizing business decisions under a variety of constraints (e.g. financial, economic, and related to the business or production processes).
This expertise, together with the possibility to access a vast collection of pre-designed scenarios and model components from our past activities, grants us the flexibility required for rapid prototyping of optimization systems. This agile approach to development is crucial for cooperating with domain experts, and for assessing in an effective fashion the benefits of introducing optimization methods in a given business context.

Strategic Planning

In a market that is becoming ever more dynamic and data-drive, the ability to take the right decisions at the right time is key to success. Software systems for business analytics can effectively enhance decision-making activities by supporting the definition of alternative strategies to achieve manager-selected goals.

At MindIT, we emphasize the importance of combining modern business analytics methods for maximum effectiveness: we employ descriptive analytics for data analysis and process characterization, predictive analytics to assess and forecast impacts, costs, and required resources, and finally prescriptive analytics to generate recommendations for the best strategies an automatic or semi-automatic fashion.

Artificial Intelligence

Our Synapse modular framework is the heart of MindIT products, and allows the integration of modern, heterogeneous, business analytics methods. Many of our approaches are powered by Artificial Intelligence algorithms, such as predictive methods based on Deep Learning, and prescriptive approaches based on the Constraint Programming paradigm.

Machine Learning

Industry is evolving to become more and more connected, with IoT technologies being deployed to produce increasingly large amounts of data. However, data does not speak for itself: Machine Learning and Data Mining techniques have proved extremely effective for the identification of recurring patterns, the extraction of predictive models, and the classification or clustering of time series. The MindIT team has extensive experience in the use of Machine Learning techniques, such as decision/regression trees, (deep) neural networks, and their combination (e.g. ensamble methods such as Random Forests) and integration. Thanks to this experience, the team is well-qualified to identify the most effective learning technique based on the considered dataset or application domain.

Business Analytics

The main strength of the MindIT team is the ability an expertise in the integration of different analytics methods, which enables more effective and efficient business solutions. The combination of descriptive, predictive, and prescriptive analytics leads to more advanced decision support systems, capable of providing the extra edge needed to make companies more competitive in the Industry 4.0 market.

Big Data

Big Data are often characterized in terms of their five Vs, i.e. Volume, Velocity, Variety, Veracity, and Value: they are produced in very large amount, with increasing frequency and speed by Internet of Things devices; the have heterogeneous nature, they often contain noise and errors, and (most of all) they should be exploited to produce actual value. The MindIT team is capable of dealing with data of this kind, which are difficult to handle and process via classical Business Intelligence methods. Most notably, the MindIT team has experience in leveraging data-driven insights and embedding data-extracted models into optimization tools: this enables the application of optimization technology in complex scenarios, with significant benefits in terms of speed and quality of decision-making activities.

The team in the last 10 years has actively worked for industies and public administrations, raising more than 2 Million Euros between projects and funding and resulting winner of 4 research awards in Artificial Intelligence.

Management Team

Alessio Bonfietti
CEO, Founder

PhD in Electronic and Computer Engineering, expert of artificial intelligence, machine learning and optimization models and algorithms. In 2013 he won the "Best Italian PhD Thesis Award" in artificial intelligence.

Federico Caselli
CTO, Founder

Computer Engineer, expert of distributed systems, data analytics, swarm intelligence and programming languages.

Raffaele Ianniello
Project Manager, Founder

Computer Engineer, expert of programming languages, machine learning, analytics, distributed systems, Fiware and GIS.

Advisory Board

Michele Lombardi
Advisor, Co-Founder

Assistent Professor at the Univerisy of Bologna, expert of artificial intelligence, machine learning and optimization models and algorithms. In 2012 he won the "Best Italian PhD Thesis Award" in artificial intelligence.

Michela Milano
Advisor, Co-Founder

Full Professor at the Univerisy of Bologna, expert of artificial intelligence, machine learning and optimization models and algorithms.

MindIT is a spin-off of the University of Bologna.

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