AI development services
– the strategic way

Artificial intelligence is a significant technological trend that shapes the web development landscape. Over the last few years, AI-powered modules have become one of the most desired features of software platforms and applications. As such, they require an adequate system architecture to work smoothly – which has a strong impact on how these systems are developed.

However, many web and mobile applications are not AI-powered and are not intended to be, at least in the near future. They can still benefit from AI-assisted development, e.g. Quality Assessment & code review.

There are certain factors that impact the final cost of such a project. These include: using off-the-shelf components, team composition, quality of data, project scope, costs of the infrastructure, integration, and maintenance, etc.). That’s why it is so difficult to assess this cost without knowing the details.

In general, the costs of AI projects vary from $10-20K for a simple Proof of Concept, which will help you validate the idea of using AI to solve a specific business problem, to $50-500K for the full implementation. The reliable estimation needs to start with having a closer look at your needs, requirements, and possibilities to assess the solution’s complexity and the work it requires.

Read more:

• How much does it cost to implement AI in an FMCG company?
• What’s the cost of artificial intelligence in healthcare?

There is no fixed team size for AI development projects. Depending on your requirements, the team composition in an AI project may vary. Also, note that the AI development team may not need to be limited to data scientists and a scrum master. If you need your AI models to integrate with a system you already use, you will need a software engineer(s). If you need to build new dashboards, interfaces, or whole apps to allow for easy use of the model, you will also need designers.

If you want to build an AI-powered web application, you need to start with designing the architecture that will make it possible to integrate various AI models.

To make it “future proof”, we suggest you not focus solely on the models that you’re starting with. Don’t focus only on the temporary needs. Instead, try to identify all the places that have the potential to be AI-powered in the future – regardless of the data you have right now or your current business processes, needs, and priorities. Thanks to that, you will be able to plan the whole architecture of that new system in a way that will make it possible to integrate other artificial intelligence models in the future.

Artificial intelligence changes web development in many ways. On the one hand, it is transforming how web apps are developed. AI-powered tools for developers can automate some tasks (therefore reducing the development time), improve the code quality, or even suggest optimizations in design based on users’ behavior. On the other hand, it requires web apps and systems to be written in a certain way that enables integration with artificial intelligence models. For sure, it is an important trend that will have a significant impact on web development.

Machine learning uses various types of algorithms: neural networks, linear regression, logistic regression, clustering, decision trees, random forests, etc. The choice of a specific algorithm should be adjusted to your project. Often, it is necessary to test a few algorithms to find the one that is most suitable for the specific use case.