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A few weeks ago, B4i participated in the AI Festival organized by We Make Future at Bocconi University.
Why did we participate? The answer is simple: as more and more startups integrate AI into their solutions, events like this serve as important opportunities to connect with ecosystem players, share insights, and stay at the forefront of innovation.
During the event, our Operating Director, Nico Valenti Gatto, highlighted B4i's role in supporting AI-driven startups and moderated a discussion with four B4i portfolio companies that are actively using artificial intelligence in their businesses:
Quick Algorithm – represented by Francesca Tosi, Head of product;
Rilemo – represented by Pablo Giaccaglia, Co-Founder & CIO, and Valentina Lidoni, Co-Founder & CEO;
Nando – represented by Chiara Incorvaia, Sustainability Consultant – Waste & Carbon Accounting.
Here are the key takeaways from the conversation.
[Francesca] I'm Francesca Tosi from Quick Algorithm, a startup specializing in predictive maintenance and energy efficiency for industrial machinery and equipment. We've developed a solution that combines IoT with an AI-powered data analysis system to process information from industrial machines. We were part of the B4i accelerator in 2020 - so we're veterans now! - and we've grown to serve over 50 industrial customers.
[Valentina & Pablo] We are Valentina and Pablo, co-founders of Rilemo. Our startup develops medical devices to capture high quality images and enable patient diagnostics anywhere. AI plays a critical role in analyzing these images and generating insights. We're new to the B4i program, having joined the latest batch, and are currently working with hospitals to validate our solution.
[Chiara] I'm Chiara, and for the last year and a half I've been working at Nando, a startup that uses AI to monitor waste production in companies and large organizations. My role is focused on supporting institutions in their sustainability journey, helping them improve waste management and reduce waste production through monitoring tools that provide data to set goals and track progress. You can even find one of our solutions here at Bocconi University: the totem you may have seen is part of our service!
[Francesca - Quick Algorithm] Investors and funds are mandated to invest in AI, and this thing incentivizes startups to incorporate AI everywhere. However, in our field - especially with our clients - overemphasizing AI can be counterproductive. The industrial sector is traditionally cautious and sometimes skeptical, so to avoid being generic, we’ve had to be extremely specific and concrete about how AI genuinely enhances our product. We demonstrate this through real use cases and tangible results that wouldn’t be possible without AI. Ultimately, clarity and concrete proof of AI’s impact are key.
[Valentina & Pablo - Rilemo] Clinicians want visibility into the diagnostic process and don't want a "black box" approach. AI in healthcare has significantly improved diagnostics and process optimization. For example, in breast cancer detection, AI is working with radiologists to reduce false positives and negatives. It also speeds up procedures such as MRI scans, reducing acquisition time by 50%, allowing doctors to treat more patients and reduce waiting times. AI also improves image quality, particularly in ultrasound, by eliminating noise and defects, allowing physicians to see more detailed anatomy. Overall, AI improves diagnostic accuracy and hospital efficiency.
[Chiara - Nando] Our whole operation is based on image recognition. We have a dataset of images, which is our "treasure", where the AI is trained to analyze and detect differences between them. These differences guide its continuous learning process, and the more images it receives, the more knowledge it gains. By working with images, our hardware captures real, actionable data. Essentially, our device is equipped with a camera that serves as the source of our knowledge. Then, all of the captured images are processed to generate data that is used by the AI.
[Francesca - Quick Algorithm] Convincing traditional industries to adopt AI wasn't easy at first. These industries are used to on-premises solutions, and many were skeptical of cloud and AI technologies. As mentioned, we focused on providing concrete examples and real use cases, but without previous customers, this was challenging. To speed up the sales process, we integrated IoT devices in our offering, allowing customers to quickly deploy sensors and analyze data within hours. This streamlined the process and reduced the sales cycle from one year to about three months. Now, with established customers in different industries like pharma and automotive, we can use these references to build trust and accelerate adoption.
[Valentina & Pablo - Rilemo] Healthcare data is one of the most valuable and protected types of information today. As a result, it's essential to develop algorithms that are inherently secure, ensuring both hardware and software protection for patient data. Data security is critical because it directly reflects the value of the user interacting with the technology. The healthcare sector in particular must focus on data protection, and there are significant regional differences in how data protection is handled - especially between Europe and the U.S. There is still a lot of potential for innovation in this area, but any solution must prioritize data protection and management as its foundation.
[Chiara - Nando] In the case of Nando, we all had prior knowledge of AI because most of us were computer engineers who had worked in the field. This gives us a significant competitive advantage because we have developed our own artificial intelligence system internally. This allows us to quickly improve it and adapt it to new needs.