From Research to Real-World: How Collaboration between AI Startups and Product Development Companies Can Create Real Business Value

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By José Ignacio Orlando

March 2, 2023

Applications of artificial intelligence (AI) and machine learning (ML) have rapidly increased in recent years, particularly in fields such as biology, healthcare, and life sciences in general. While many research studies are published in top-ranked scientific journals, only a few turn into actual solutions that improve people’s lives. Most of these investigations remain confined to papers, small evaluations or experimental code, without ever making it to real-life solutions. As Pau Labarta Bajo, a Spanish freelance expert in ML/AI rightly points out, “Your ML model, no matter how accurate it is, has a business value of $0.00, as long as it stays confined in the realms of Jupyter.”

As long as your ideas and models stay in a theoretical capability, they won’t be able to deliver tangible value.

The main reason behind this issue is the isolation of the research ecosystem from product development, mostly due to the large technological gap between ideas and implementation. Only big AI companies such as Google, Apple, Amazon, OpenAI, or Microsoft, which have access to massive computational capabilities and specialized human resources, are currently able to generate cutting-edge AI solutions from a lab bench to production.

This is in stark contrast to startups and scientific spin-offs, which are at the edge of research and development. Often owning innovative ideas and even AI-based proof-of-concepts and MVPs, they still frequently lack the resources to scale them up to real-life solutions. This is linked to the way in which startups grow and get their funding. In most cases, they have access to short-term investments from venture capitalists that they have to spend fast to accomplish their goals and guarantee themselves access to a next round of investment. As they cannot ensure a continuous investment flow, they frequently face limits when it comes to hiring the highly specialized teams necessary to scale their ideas, turning into freelance networks with no cohesive development processes.

Does that mean then that only big tech companies are going to be protagonists of this revolution? Not at all. Product development companies such as Arionkoder can certainly come into play to alleviate these issues. By partnering with us, startups can get actual business value from their scientific ideas and significantly accelerate their process toward real-life solutions. We can provide them with the infrastructure, resources, and expertise needed to push their proof-of-concepts one step further, turning them into scalable and profitable AI solutions, at a lower risk and with the required flexibility.

Product development companies have experience in taking ideas from concept to production, and they already have the necessary human capital under their roof. This means that startups can outsource their scaling tasks to them, and focus on the main picture, such as setting the scope and requirements, auditing the solutions and proposing new ways to improvements. 

In conclusion, the rapid advancement of ML is transforming various industries, but it’s crucial to note that scaling up these innovations requires more than just ideas and prototypes. By bridging the gap between research and development, product development companies such as Arionkoder can help startups and scientific spin-offs to turn their proof-of-concepts into profitable and scalable AI solutions that can significantly impact people’s lives. 

Arionkoder is a product development company that specializes in developing digital solutions and AI for businesses. Our team of experts has the skills and knowledge needed to help startups scale their ideas and turn them into profitable and scalable AI solutions. If you are a startup looking to scale your AI-based ideas, contact us at today to discuss how we can help you to achieve your full potential!