POC, MVP, Production : the key stages of an AI project

Introduction

Artificial intelligence is revolutionizing many business sectors, opening up new opportunities for companies.

However, developing an AI project that can be easily industrialized requires a high-performance platform. With the ALLONIA platform, all AI projects are quick and easy to set up. Our sovereign, secure and collaborative platform makes it possible to carry out any AI project from start to finish.

To meet this challenge, it’s important to adopt a structured and rigorous approach, based on three key stages: proof of concept (POC), minimum viable product (MVP) and production launch.

The POC (Proof of concept)

The POC (Proof of Concept) is an important stage in validating the feasibility of an AI project. It involves developing a simplified prototype to test the key concepts and demonstrate its technical viability.

The objective of the POC is :

  • Validate hypotheses : Confirm that the technologies and approaches chosen correspond to the needs of the project.
  • Identify technical challenges : Detect potential problems and obstacles to be overcome before proceeding with development.
  • Get buy-in from stakeholders : Convince decision-makers of the project’s potential and secure their financial support.

The POC is important for several reasons :

  • Reduce risk : The POC allows the idea to be tested before investing significant time and resources in full development. It also allows any problems to be identified and corrected before they become too serious.
  • Improved decision-making : The POC provides concrete data on performance. This data enables stakeholders to make informed decisions about whether or not to continue with the project.
  • Gaining confidence : The POC helps to convince stakeholders of the potential of the AI project. It can also be used to generate enthusiasm for the project among end users.
  • Encourage learning : The POC is a learning process. It enables the project team to better understand the challenges involved in developing an AI platform and to refine its strategy.

Minimum viable product (MVP)

The MVP is a simplified version of the AI project that offers the essential functionality to meet users’ needs. The aim is to build a functional and usable product as quickly as possible, in order to gather initial feedback from users and iterate quickly.

The MVP’s objective is to :

  • Test key functionalities : Validate essential functionalities and their usefulness to users.
  • Collect user data : Gather valuable information about user behaviour and needs.
  • Improve the product iteratively : Adjust based on user feedback, adding or removing features.

Going into production

Production launch marks the deployment of the AI project in its final environment. This stage involves setting up the necessary infrastructure, training users and monitoring performance.

The aim of the production launch is to :

  • Deploying the project : Providing users with a high-performance, secure and sovereign AI platform like ALLONIA’s is a real plus. Indeed, ALLONIA’s platform enables your teams to go into production in just a few clicks !
  • User training : Train your users to use the platform. Our ALLONIA platform is quick and easy to learn. Our platform has been designed to simplify the user experience. And even if it’s easy to get started, internal documentation is available to help your technical teams.
  • Monitor performance : Track your project’s performance and identify opportunities for optimization. With our platform, you can do all this in just a few clicks !

Find out more about ALLONIA

The SaaS artificial intelligence platform that accelerates and secures ALL your AI projects. Whether you’re a large enterprise, SME, ETI or public organization.

From POC, MVP to production launch, the ALLONIA platform meets all 3 demands! And, since June 2023 integration of generative AI !

Conclusion

A successful AI project requires a structured and rigorous approach, based on the key stages of POC, MVP and production launch. By following these steps, companies can maximise their chances of success and create and deploy high-performance AI projects that meet business needs and issues.

In addition to the points mentioned above, it is important to note that :

  • The choice of development methodology must be adapted to the specific needs of the project.
  • It is important to establish clear governance for the AI project, defining the roles and responsibilities of the various stakeholders.
  • Communication is essential throughout the project, to ensure team cohesion and the alignment of objectives.