Artificial Intelligence Development Services

There are lots of popular AI-based solutions that companies and individuals use every day – for example, a fraud detection detection tool, a virtual assistant, social networks algorithms, image recognition features, biometric authentication, etc. Artificial Intelligence development companies like Fively build and implement AI applications for clients from different industries, such as Healthcare, Education, Real Estate, eCommerce, Insurance, FinTech, Cybersecurity, and more.

These areas are the most important in the current Artificial Intelligence development:

1. Machine Learning: handling datasets with computer systems and algorithms.
2. Deep Learning: going deeper into several data layers to get more results.
3. Computer Vision: analyzing data in the form of videos and images.
4. Natural Language Processing: analyzing human languages in various forms like voice and text.
5. Expert Systems: applying AI development services to create tools for diagnostics and recommendation giving.
6. Predictive Modeling: analyzing statistical info with AI-powered technology to make predictions of various business outcomes.
7. Neural Networks: applying all advantages of AI product development to analyze the given info to generate and connect things.

AI is an important trend in modern technology that has a huge impact on web development. Companies across various industries want to use the many benefits of AI-driven development, creating such features and modules for new platforms. Therefore, experienced AI developers are in high demand. One of the crucial requirements is knowledge of architecture that allows to engineer stable and smoothly working solutions. In addition, modern web and mobile development can greatly benefit from using AI-powered tools for code review and quality assurance.

The choice of coding languages in AI software engineering depends on how developers use computer systems. For example, Python is the best for Machine Learning in particular and data analysis in general. Java, Prolog, Haskell, and C++ are also very efficient for AI-driven software development.

Data scientists may use a variety of algorithms – for example, decision trees, logistic and linear regression, clustering, random forests, and more. Needless to say that deep knowledge of most popular algorithms and practical experience with their application are critical requirements for an AI software developer, because this choice is an important part of the process. Typically, developers test several options to select the one that best fits your project.

There are various challenges associated with custom software development, especially when building an AI solution.

1. Inaccurate data. If you want to get correct results without critical mistakes, it is important to use quality data that is also well-structured.
2. Difficulty of training. It takes a knowledgeable and experienced AI software developer to train models and create the right algorithms.
3. Handling and storage of data. In order to avoid vulnerabilities and protect sensitive information from cyber attacks, you should invest in a secure data management environment.
4. AI integration. It is difficult to integrate a new AI-driven solution into your existing system, but AI software development companies normally have successful cases of such integration and process automation.

AI services include a variety of ways to use Predictive Modeling, neural networks, Machine Learning, and other advanced ways to automate repetitive tasks, solve various business problems, analyze huge datasets in real time, predict possible outcomes, support process automation, and generally make everything faster and more effective.

The big five of such companies are Apple, Google, Microsoft, Meta, and Amazon. It is not a mistake to say that every huge tech company actively implements AI-based solutions. There are also world-known companies like AKASA and Robust Intelligence that enable artificial intelligence development services for their B2B partners. If you want to develop a new AI solution, you can choose from providers that offer the most relevant price-quality ratio for you. The important factor is whether your tech partner has a relevant portfolio with AI development projects.

Yes, it is possible to create your own AI. The first and most important question that you should ask yourself is what kind of problem you want to solve by AI development. Next step will be collecting the relevant data to train the model for your AI solution. AI software design, engineering and implementation require a deep understanding of Machine Learning, Data Science, and other related fields.

Coding skills are necessary if you are developing an AI-driven project with complex architecture. As a rule, developers have hands-on experience with a programming language (for instance, Python or C++) when they start building custom AI software. On the other hand, the current level of codeless technology allows you to develop simple AI-powered projects using platforms like DataRobot or Google AutoML. We recommend you to define your business goals first – it will help you decide what exactly you want to achieve with AI, because creating a simple chatbot for a small eCommerce store and engineering a complex fraud detection tool for an insurance company will be entirely different projects.

The cost may be greatly influenced by these 3 factors:

1. Complexity. The cost of development and implementation depends on how complex the project is. Think about the architecture and algorithms. You should also bear in mind amounts of data and whether it is structured properly.
2. Core features. Off-the-shelf AI applications cost less but may not cover all the features you need while custom AI software is built from scratch and therefore tailored to your business requirements.
3. Cooperation details. These might be defined by project managers and include things like the scope of work, size and location of the team, the employment type (outsourcing or in-house, for example), required time to complete your project, etc.

The size and composition of AI app development man vary, depending on your project requirements, complexity, deadlines, etc. Basically, the number of required specialists is the same as it would be with making any other custom software, like SaaS development services or workflow automation services. The shortest list of team members will include 1-2 data scientists, a QA engineer, and a project manager. In case there are complex user flows and interfaces involved, you will also need a UX/UI designer. When you partner with an AI software company, they normally study all specific things of your project and define which specialists should be in a team to complete the project on schedule and reach all the goals.