There is a statistic showing that, on average, only 3% of a software’s available features are actually used.
Why? Because there are too many functions, often complex, difficult to navigate, and even harder to fully use. B-AI Semplice is called “simple” for a reason: we want to make Business Intelligence easy to use.
And where good software design alone cannot simplify things further, we rely on artificial intelligence.
That is why B-AI Semplice integrates AI directly into the user experience, helping users read data, interpret it faster, and turn it into operational insights.
This is the logic behind integrating artificial intelligence into the first ready-to-use Business Intelligence solution for logistics and transport. Not to add another layer of complexity to BI, but to do exactly the opposite: reduce the time needed to read data, interpret dashboards, and turn numbers into operational guidance.
Because very often the problem is not having data. The problem is being able to read it properly, quickly, without getting lost among charts, filters, indicators, time comparisons, and increasingly deep levels of detail.
A well-designed dashboard can contain a huge amount of valuable information. It can show trends, anomalies, critical issues, variations, concentrations, performance indicators, deviations, and recurring patterns. But for this very reason, it also requires attention, method, and time.
Integrated artificial intelligence inside BI was created to make this work more accessible.
How the integrated AI works
Inside every dashboard there is a dedicated artificial intelligence icon.
By clicking it, the AI analyzes the data contained in the dashboard and returns a structured interpretation of what emerges from the charts. In practice, it does not simply describe what is visible. It helps the user understand where to focus attention.
This is an important step because an advanced dashboard is not always meant to be read from top to bottom. Very often, the real value lies in the details, in the less obvious deviations, in comparisons between periods, in recurring anomalies, or in signals that begin to emerge before they become evident problems.
The AI helps identify areas of attention, critical issues, anomalies, trends, and recurring patterns. It does not make decisions in place of the user, but guides them in reading the data.
It is like having an analyst perform an initial scan of the dashboard and say: “Look here, this deserves attention.”
For people who use BI every day, this means saving time. For those who are not used to navigating complex dashboards, it means reducing the distance between data and decision-making.
From chart to report, without starting over every time
The analysis generated by the AI can also be used as a foundation for reporting.
The generated texts can be copied and pasted into documents, emails, periodic reports, or presentations. Likewise, the charts displayed in dashboards can be downloaded as images and inserted into presentations such as PowerPoint.
This makes it easier to prepare internal updates, operational meetings, or management reports.
The value is not only in having the data available, but in being able to quickly transform it into content that is understandable, shareable, and useful.
Because very often the slowest part of the work is not analyzing a number, but explaining what it means.
With this feature, B-AI Semplice helps users move more quickly from dashboard to communication of results.
Querying data in natural language
Alongside the automatic dashboard analysis feature, B-AI Semplice also integrates a second way of using artificial intelligence, designed to query data through conversation.
Inside the administration area there is a button that activates an AI chat. From there, the user can select the dashboard they want to work with and start a real conversation with the data.
The user can ask the system what kinds of questions can be asked about that specific model. In this way, the AI shows which KPIs are available, which information can be queried, and which dimensions can be analyzed.
This step removes one of the most common problems when using analytics tools: not knowing where to start.
Instead of having to know the structure of the data model in advance, the user can directly ask the system what kinds of analysis can be performed. From that point, the interaction begins.
Users can ask questions in natural language, receive answers about available KPIs, explore specific data points, change perspectives, create comparisons, and continue the conversation without translating every request into technical filters or complex queries.
Creating charts directly from the chat
The AI chat is not only for asking questions. It can also be used to build new analytical elements.
The user can ask the system to create a chart based on available data, select the most suitable visualization type, download it, or add it to an existing dashboard or to a completely new dashboard.
A logistics or transport manager can start from a question, receive an answer, turn it into a chart, and save it as a new monitoring element.
Without having to build everything from scratch, without depending on a technician every time, and without interrupting the flow of analysis.
Business Intelligence becomes more dynamic because it is no longer limited to displaying predefined dashboards. It allows users to create new views starting directly from their questions.
Conversations with the AI are saved, meaning that a chat can be resumed later without losing the context of the analysis already started.
This is particularly useful when working on recurring analyses, preparing meetings, following a topic over time, or returning to reasoning already started. Having an accessible history creates continuity in analytical work instead of forcing users to restart every time.
Recurring questions become easier
Another useful feature is the ability to create sample questions. These are the questions users find themselves asking every week or every month, perhaps for a report, a recurring meeting, or a management review.
Instead of rewriting them every time in a complex way, they can simply be saved and reused when needed.
It may seem like a small detail.
In practice, it reduces daily friction and makes the platform feel more natural to use. Because simplicity is not made only of big features, but also of small unnecessary steps removed.
Less time spent rebuilding the question, more time spent understanding the answer.
The platform also allows the creation of additional models, progressively expanding the scope of available analyses.
This makes it possible to adapt the use of artificial intelligence to the company’s needs, available data, and the business areas that need to be monitored.
The logic always remains the same: make data more accessible, readable, and queryable.
Not to build a BI platform for a few specialists, but a tool that can be used by people who need to make decisions, monitor performance, prepare reports, and identify critical issues before they become problems.
Artificial intelligence should simplify, not impress.