Starting an AI company is not possible with only a good idea. Most likely, you’ve noticed this yourself. The difference between those who get a second round and those who fail is how fast they can bring their product to users. You can’t afford to wait half a year for the whole process. Even if it’s in the early stages, you should look for something that works. This is why an MVP is important.

The thing is, most teams don’t handle this step well. It is especially important in the field of AI. Why? AI applications are not constructed in the same manner as other apps. Having a working MVP for AI requires taking care of models, data, and dealing with unexpected outcomes from the outset. You can’t make up for a lack of understanding with complicated tools. What you need is something that can be built fast, checked easily, and provide feedback right away. For this reason, selecting the right development partner is one of the most crucial choices you have to make in the beginning. Companies like DBB Software have shown how much difference the right team can make at this stage.

Why AI Startups Need Specialized MVP Development

AI MVPs are not the same as other MVPs. Almost any developer can assist you with making an app that includes a form and some buttons. Yet, AI is not always easy to deal with. At times, the system functions properly, but sometimes it doesn’t, and that is expected. You handle training multiple times, data with errors, and models that need to be adjusted. You’re not only concerned with creating features. You are trying to see if your main idea can work as you imagined it. That is a whole new situation. It requires different guidelines.

Using your MVP lets you see if your idea will really work in practice. It doesn’t make sense to spend time on advanced techniques if nobody is interested or if they do not work with real data. A smart MVP team knows that aiming for perfection is not the goal. They provide a simple, focused, and helpful way to ship your product, so you get actual feedback. This is the only method to find out what needs improvement, what should be let go of, and what should be scaled up.

What to Look for in an MVP Development Partner

Many companies that develop apps are unaware of AI. This creates a challenge, since a strong AI MVP involves product strategy, quick solutions, and dealing with uncertainty. If your partner doesn’t have experience, they might slow you down or develop the wrong solution. You should look for a team that knows the basics of AI and can use them effectively in development. Therefore, what are the most important things to check?

• Using AI technology in products that are not limited to simple chatbot add-ons.
• Knowing what to focus on at the beginning, such as speedy testing, simple delivery, and limits to the budget.
• A good understanding of TensorFlow, PyTorch, and Hugging Face frameworks.
• Being able to go beyond the job and give feedback to help improve the product.
• Working with data pipelines, the cloud, and deploying models.
• Clearly explaining things and providing updates that are organized and truthful.

Top 15 MVP Development Companies For Startup

Getting the right partner for your MVP is a tough decision, especially when AI is involved. Therefore, these are 15 companies from the US and Central Europe that provide the expertise needed to get AI products rolling. They are not just any run-of-the-mill development companies. They have actually built MVPs with AI, not only experimented with it. We’ll begin by looking at the five that are always in the spotlight.

1. DBB Software (Poland / Ukraine)

DBB Software focuses purely on product delivery and early-stage MVPs. Their biggest advantage comes from their internal library of tech tools, called DBBS Pre-Built Solutions, which allows them to cut development time by half. That figure isn’t part of marketing, as it’s based on having the same user authentication, dashboard, and model testing processes every time. They have developed AI systems for healthcare and logistics using NLP and processing data in real time. If you aim to ship your app fast and get real user feedback, DBB knows how to do it without wasting your time.

2. Netguru (Poland)

Netguru is famous for building nice-looking websites, but they have also been active in the AI field. Members of the company have been involved in creating automated tools, dashboards for predicting finances, and platforms for managing energy efficiency. Netguru manages to combine good design with actual machine learning usage, which is a challenge for the majority of teams. They use well-planned delivery sprints and well-organized reporting. When your MVP project requires UX and AI from the beginning, they are the right choice.

3. Waverley Software (US / Ukraine)

Waverley is an American company that started from strong engineering foundations in Eastern Europe. Some have delivered AI-powered MVPs for use in the smart home, wearables, and telehealth. Their AI experts carry out time-series forecasting, observe user actions, and use computer vision technology. They differ from others because they know what the product should do and how to make it happen. They won’t focus only on your wants; they’ll also care about what the model needs. That way of thinking helps the project start on the right path.

4. Ciklum (Ukraine / Central Europe)

Though Ciklum is a big company, they have made room for startups by focusing on AI and research and development. They have made it possible for teams to use NLP engines, recommendation systems, and forecasting tools. They are strong because they can place experts with your startup to help you move forward according to your plans. People with a data strategy who wish to bring their idea from a prototype to an MVP and further to a platform can rely on Ciklum.

5. SoluLab (US)

The company has worked on AI MVPs that include voice technology, chatbots, and AI-powered CRMs. All their processes are simple, and the build phases they follow are clear and can be tracked. Though their headquarters are in the US, they provide their services around the world with distributed centers. They have used GPT technology and tools for content, automated sales, and smart tagging. They show how startups’ flexibility can blend with the structure needed for large projects, which is very beneficial if you want to work fast without losing control.

10 More MVP Companies Worth Considering

Build Fast, But Build Real

Founders usually don’t talk much about what happens when issues come up with their development partners. Even so, it is significant. AI MVPs may sometimes act differently than what was expected. At times, the model doesn’t work as expected, and other times, the data isn’t satisfactory. That’s normal. The important thing is for your team to spot the problem early, take responsibility for it, and make changes promptly. Ask them for their experience with similar situations. If the answer you get is unclear, continue your search.

Try to include users in the process as early as possible. The goal isn’t a perfect product, but rather an idea that has been proven. If you have a good team, they will help you put out a simple working version and observe user feedback. At that point, we begin to learn. That’s the source of true value. Therefore, make your instructions easy to understand, aim for fast solutions, and hire people who can deal with errors in your AI. It won’t, and that’s the purpose of creating an MVP.