The approach that seems most common to what we know as AI is that of a solution in search of a problem. Our approach is the opposite: we start from the problems to look for the best solutions to solve them. We are aware that humans sometimes get distracted and tired, but, unlike machines, they are capable of understanding the deep meaning of things and finding creative solutions to new and old problems. For us, the machine is a kind of exoskeleton that greatly enhances the capabilities of the human operator. The human operator instructs the machine to perform certain tasks, following very precise sequences, without leaving room for improvisation. It is the human who must always have the last word. We do not need a machine that is omniscient as proponents of AGI would want. In our view, natural language is just a way of interfacing with the user, making our solution accessible to anyone because they can use their everyday language. Beyond that, it should limit itself to extracting from the conversation the information necessary to initiate a search and to select the most relevant results. This will allow us to extrapolate information from emails, electronic calendars, and only need to check with the client to confirm that everything we have 'intuited' from this work matches their real needs and to provide them with the possible solutions that best meet these needs, already knowing their personal tastes, the context in which they will travel; indeed, they do not choose the same services if traveling alone for work or with the family, and the corporate travel policy. Interaction times with the client should always be as short as possible, because we believe that they can invest their time better and that we can do this job better and with fewer chances of making mistakes, as professionals in the field with continuously updated technical knowledge not in the public domain.

Regarding so-called back-office work, it's not necessary to possess great intelligence but rather sufficient to follow standard preset instructions, complemented by more specific ones provided by the client. For instance, one doesn't need to be a genius to understand that, in an itinerary that includes a flight with a layover, the preferable solution will always be the one that doesn't require changing airports and offers shorter connection times. Essentially, the so-called AI will need to strictly follow the precise instructions given to it, with the difference that its capabilities will allow it to be faster and more accurate in selecting the best available options compared to any human operator. It will be completely precluded from having even the slightest possibility of being creative. When it is unable to respond because it encounters an uncoded situation, it will need to defer management to the human operator, who will be allowed to use creative talents to find a solution. Subsequently, this creative solution could be coded and managed autonomously by the machine, should the situation arise again.

Regarding the so-called AI, many wonder if we are facing a new speculative bubble. We cannot speak for others, but as far as we are concerned, we do not believe this to be the case. We have said that we start from a careful analysis of problems to look for solutions. Therefore, it is very difficult for us to fall into one of the biggest reasons for startup failures, which is 'No Market Need'. Even though initially we will focus on some specific markets and functionalities, our market is global; as, mutatis mutandis, the needs are the same everywhere. This makes it less likely to encounter another possible reason for failure, the 'Lack of product-market fit' (PMF). We advocate for a frugal approach to what we know as AI, for two reasons: economic and environmental. Indeed, we are mindful of costs and do not want to wastefully burn through computing power, as we want our creation to be profitable from the start. We also know that computing capacity has negative repercussions on the environment. Since in choosing the flights we are going to propose, we are also asked to consider their environmental impact, we could not do this by ignoring or making others ignore how we are directly affecting it. For us, transparency is also important, starting with how the algorithms we use function. It should always be possible to easily explain their operating mechanisms, and they should be as bias-free as possible.

Transparency will also be the foundation of our relationship with customers. Everything must be set up to achieve alignment between the customer's interests and ours. Experience teaches us that the remuneration model most in line with this is the service fee and subscription model, rejecting any form of remuneration and/or incentives from suppliers. Many operators in the sector leverage the lowest price; we, on the other hand, want to leverage clarity and transparency. We too can offer some of the most economical rates available on the market, sometimes even cheaper than those of the competition, but in doing so, we always make it a point to inform in advance that, almost always, a cheaper rate equals a more restrictive rate in terms of the possibility of making cancellations and voluntary changes by the passenger. We do not offer these rates without first providing this necessary warning and, above all, we do not propose the sale of a 'Cancel for Any Reason' policy afterward. In cases like these, we immediately propose a higher rate which, in the event of voluntary cancellation by the client, can be fully refunded, without applying any deductible.