Artificial Intelligence Consulting

How ML cube can help

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Do you want to accelerate the AI transformation journey of your business, but don’t know where to begin?

Get started with ML cube

Use Case Definition Data Preparation AI Model Development

Identify use cases that can impact your business. Analyze the value of each cases. Prioritize your use cases.


Most machine learning algorithms require data to be formatted in a very specific way, so datasets generally require some amount of preparation before they can yield useful insights.


With our in-house team of AI consultants, we work across the entire stack, with an end-to-end approach, to develop AI-powered systems for the customers, and guarantee the maintenance of high standards performance of their systems over time.

We've got it all covered

Our in-house, collective skillset and experience allow us to develop AI projects end-to-end: we will take care of your entire project from business framework to KPIs, from data preparation to scalable deployment and production.


Scoping & Architecture Design

We understand your goals and analyze your business requirements: We investigate to determine whether it requires a ML solution. We work closely together to define KPIs, prepare a road map, review scientific literature and determine requirements.

Project Setting & Governance

We make a decision about introducing AI in your business: If positive, we gather the requirements and prepare a plan for your project, with milestones, deliverables and specific deadlines. If not, we save you time and money by not implementing AI.

Data Exploration

We explore robustness and completeness of available data If you have sufficient data ready for collection and analysis, that’s perfect! If not, we will collect them in any way possible. Once data are available, we perform an exploratory analysis phase to find patterns and correlations.


Model Developement

Kick it off! We run thousands of parallel experiments to develop an AI model. A model is the core of an algorithms system – trained on historical data it can predict future trends or understand the semantics of a text.

Data Collection & Storage

Perform it… We perform state-of-the-art scraping, with our sound expertise in sourcing data: from the web, documents, databases and APIs. We also do crawling and build bots which automatically achieve our clients’ tasks.


…Productize When we get the proof that our prototype model can address your business problem, we will launch it in production. We'll integrate the model with your application and provide support services to make sure it works on a broader data set.
Our management process is designed to minimize organizational overhead and avoid information mismatching.
The documentation produced at each step allows to capitalize the experiences and to reuse part of the work done for other future scenarios.
The trial step is independent of the productization, so you can decide to proceed after observing the forecast test’s quality.
A structured and modular approach

Our Project Management

Phases Activities Documentation Methodology

Phases Withouttime, ML cube

  • Requirements analysis
  • KPIs design (metrics & measures)
  • Critical issues Identification
  • Data set extraction and analysis
  • Alignment with IT and Business regarding normalization strategies
  • Accuracy report processing
  • Software Development and setting
  • Role-based access control or role-based security
  • Training
  • Check KPIs results
  • Identification of improvements and new features
  • Use case description
  • Dataset report
  • Requirements report
  • Accuracy report
  • SW technical documentation
  • Overall scenario report
  • KPI results and appraisal
  • At every stage of the journey, we will formalize every decision, objective, analysis and result to improve the understanding of the project and the sharing of choices
  • We guarantee a close collaboration with the client's key resources and a thorough training course for the entire journey
  • Modern data analytics technologies require rigorously quantitative application methodologies to ensure a perfect alignment of interests between supplier and customer.
  • For this reason we invite our customers to deliver the complete dataset only after having received the red-list at the end of the trial project.

Unique End-Point

No organizational overhead, close business requirements alignment, strong project commitment.

1, ML cube

  • High organizational overhead
  • Need of AI expertise
  • Difficult to obtain a unique product (customized vs competitors)
  • High licensing cost

2, ML cube

  • Framework standard ≠ Product standard
  • Need of AI expertise
  • Risk of «on-demand development» (innovative technologies with stuffy approach)

3, ML cube

  • No development overhead
  • High skills & experiences
  • Project commitment
  • Unique and integrated solution
  • Direct relationship with the business and with the IT function

Our Artificial Intelligence Expertise

AI Areas

Machine Learning, ML cube

Machine Learning

Make accurate predictions and decisions from historical data.

Reinforcement Learning, ML cube

Reinforcement Learning

Maximize the return in a sequential decision problem.

Transfer Learning, ML cube

Transfer Learning

Reuse acquired knowledge to learn new tasks.

Game Theory, ML cube

Game Theory

Learn multiple decision strategies in complex scenarios.

Deep Learning, ML cube

Deep Learning

Execute complex tasks by learning from a huge amount of raw data.

NLP, ML cube


Extract valuable insights from large amounts of textual data.

Economic Sectors

Service E Commerce, ML cube


Improve sales strategy by understanding clients’ needs.

Shop 5108921 1920, ML cube


Boost advertising campaign profits for both marketers and publishers with our state-of-the-art AdOpt system.

Service Pricing, ML cube

Dynamic Pricing

Optimize pricing strategies dynamically under complex market conditions and classify end clients.

Service Automotive, ML cube


Learn driving policies in complex settings scenarios throughout interpretable Machine Learning models.

Service Banking, ML cube


Adopt Online Machine Learning approaches for Financial and Risk Management problems such as Portfolio Optimization.

Service Industry, ML cube

Industry 4.0

Solve industrial issues by combining our advanced ML solutions with Optimization Techniques (e.g. predictive maintenance and warehouse optimization).

Service Energy, ML cube


Enhance power consumption efficiency and predict failures in smart energy systems.

Service Healthcare, ML cube


We provide Online Machine Learning tools for personalized medicine, clinical trials and healthcare resources optimization.

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