We need to start by bringing some clarity, above all at a moment like this, when Artificial Intelligence is on everyone’s lips. What do we truly mean by Artificial Intelligence?
Too often, simple data mining processes (the extraction of information from large quantities of data) get passed off as Artificial Intelligence. In reality, this term refers to a machine’s ability to perform tasks that are usually performed thanks to human intelligence.
All this to say that it is a technically very complex, multi-faceted world, and that the number of challenges arising, both computationally and in terms of resources, is constantly growing. Just think that under the umbrella of Artificial Intelligence we can list a long series of specialisations: machine learning, deep learning, natural language processing, speech to text, text to speech, image recognition and so on.
An Artificial Intelligence startup VS Artificial Intelligence in a startup
There is a substantial difference between launching a pure-AI startup, making AI its core business, and using AI inside a startup. This difference can be summed up as the amplification of all the challenges and problems tied to doing Artificial Intelligence every day.
Let us see, then, what the main challenges are that a startup can run into when it wants to create a product largely based on AI.
First of all, several very vertical, specific skills are required, which are also hard to find and call for alternative engagement strategies. Think of the need to place, alongside the development roles, new professional figures such as data scientists, data engineers and machine learning experts, each of whom has more often than not taken a different specialisation path (doing NLP, and thus analysing natural language, is very different from analysing images).
A sore point concerns infrastructure costs, such as those for using GPUs, whose price has lately shot through the roof because of cryptocurrency mining. These processors are used for training models based on neural networks, or even just to accelerate their execution.
Doing Artificial Intelligence takes time, both in research and in development. Time a startup rarely has, above all in the initial go-to-market phase. This intrinsic slowness obviously clashes with the rapid obsolescence typical of cutting-edge, continuously evolving technologies. The risk of investing resources in a product that becomes obsolete the very moment it reaches the market is extremely high.
How do you face all these challenges if not with adequate investments to support growth and scalability? Just look at the rounds closed by pure-AI companies, like Hugging Face, which since 2017 has already raised more than $60M, or Jarvis.ai, with more than $6M between 2020 and 2021.
Fortunately, a good part of the difficulties mentioned above are mitigated by the presence of a strong, active worldwide community gravitating around AI, which leans heavily on the concepts of Open Source and sharing.
Artificial Intelligence as a SaaS’s added value
If, then, it is very hard to make AI a startup’s core business, how can it be employed inside a product, in particular a SaaS?
I believe the key to this problem is employing Artificial Intelligence as an enabling element of a piece of software, serving to add new features or enrich existing ones.
AI can be used to simplify the user experience while navigating an interface, using, for example, natural language processing (NLP) to show the user summaries of texts that are long to read, or highlighting in the text the main entities identified, to ease comprehension.
What’s more, since the cost of computing and using AI services is high, a SaaS’s scalable pricing logic lends itself well to optimising this aspect, allowing certain features to be enabled only in the higher subscription tiers.
And so, making Artificial Intelligence modular in a SaaS favours the enrichment of the offering and the adoption of an extremely scalable business model.
How do we use Artificial Intelligence at Startup Bakery?
At Startup Bakery, Artificial Intelligence is one of the ingredients at the base of our recipes, used to add value to every startup’s SaaS.
Our technology framework, in fact, beyond containing components and services to speed up MVP development as much as possible, also makes high-value Artificial Intelligence services available to the startups.
But that’s not all… the Startup Bakery team is working on QuSeed, a proprietary software to ease data analysis in support of investment decisions.
QuSeed takes in data of various kinds (structured and unstructured) from different sources and processes it to offer Business Analysts and Investment Managers precious insights on the investment and acquisition trends tied to the world of innovation.
QuSeed makes use of a proprietary NLP pipeline for natural language processing, as well as neural networks and mathematical models for extracting information from numerical data.
To conclude, at Startup Bakery artificial intelligence is the cherry on the cakes, there to bring immediate value and innovation to the users of our SaaS.
Startup Bakery is the Italian startup studio specialised in creating B2B SaaS companies with Artificial Intelligence. We offer aspiring Co-Founders the opportunity to develop a business idea. We create investment opportunities for Professional Investors. We help companies in their innovation process.