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If you want to wow the investors or your customers, you should shift your gaze to AI software. AI-powered software can automate your business processes, improve decision-making, and help you achieve your business goals faster. AI apps are already used to analyze customer behavior, predict sales trends, and automate marketing campaigns.
As an entrepreneur, I see so many potential benefits of investing in AI software development. Actually, I already did. With the release of Stable Diffusion in 2022, more and more AI-based products started to explode, and together with the Uptech team, we jumped into this rabbit hole and created Dyvo.ai app.
I know firsthand the challenges that come with building AI software, and today I’d like to share my experience. I’ll explain how to build AI software in 6 steps, why investing in AI software development is worth it, share the insights of Dyvo.ai development, and suggest some non-cliche AI-powered startup ideas. Let's dive in!
First of All, Why is AI Software Worth Investing In?
The answer is simple: AI software can automate your business processes, improve decision-making, and help you achieve your business goals faster. According to a report by Accenture, AI has the potential to double the economic growth rate of some developed countries by 2035. In addition, the global AI software market size is expected to reach $126 billion by 2025.
AI algorithms can process large amounts of data faster than humans and provide more accurate results. For example, AI-powered chatbots can handle customer inquiries 24/7, freeing up human resources to work on more complex tasks. AI software is already used to analyze customer behavior, predict sales trends, and automate marketing campaigns.
With so many potential benefits, investing in AI software is a smart move for any startup looking to gain a competitive advantage.
Uptech Tips to Build AI Software
Based on my experiences developing Dyvo.ai, I learned some lessons on how to make an artificial intelligence app. Here are 3 tips I'd share with everyone who wants to start an AI-based product.
Tip #1: Use machine learning to train your system
Machine learning is a powerful tool for building AI software. It allows you to create systems that can learn and adapt over time, improving their accuracy and performance.
Tips #2: Be ready to learn fast
AI technology is so fast-changing, so it's important to have a team of developers who can react and adapt to changes fast. Learning fast and integrating the knowledge into the AI software you develop – is the key. This will help ensure that your system is up-to-date.
Tip #3: Work with experienced AI developers
AI software development can be complex and challenging, so it's important to work with experienced developers who have a deep understanding of AI technology and learn fast.
How To Build AI Software: 6 Key Steps
Now, let's talk about how to build AI software. The development process is similar to building any other software application but with a few additional steps.
Here are 6 main steps you should follow. Note that I focused on the AI-specific development parts. If you want to find out more about other stages of product development: Product discovery, UX&UI design, and QA, check out our blog. We have many handy tips on these topics.
Step #1: Identify the business problem you want to solve with AI
Before you start to build AI software (any software, in fact), you need to identify the business problem you want to solve. Specifically, in AI software development, it will help you determine the type of AI technology you need to use, whether it's machine learning, natural language processing, or computer vision.
Uptech tip: Involve key stakeholders from different departments and conduct Product Discovery to gain a better understanding of the problem and business needs.
Step #2: Gather data
AI software needs large amounts of data to learn and make accurate predictions. You should gather as much data as possible related to the business problem you want to solve.
Uptech tip: Ensure that the data is diverse and representative of the real-world scenarios the AI model will encounter.
Step #3: Choose an AI technology
Once you have the data, you need to choose the AI technology that best suits your needs. There are several AI technologies to choose from, such as machine learning, speech recognition, natural language processing, machine learning, augmented reality, and many more.
Uptech tip: Evaluate different AI technologies based on the specific problem you are trying to solve, and not just based on the hype. Plus, choose a technology that has good documentation and support to ensure that you can get help when you need it.
Step #4: Build and train the model
After choosing the AI technology, you need to build and train the model using the gathered data. This is a complex process that requires expertise in AI and data science.
Uptech tip: Monitor the model's performance throughout the training process and adjust it as needed.
Step #5: Test the model
Once the model is built and trained, you need to test it to ensure that it's accurate and reliable.
Uptech tip: Use different evaluation metrics to measure the model's performance, not just accuracy.
Step #6: Deploy the model
Finally, you need to deploy the model in a production environment where it can be used to solve the business problem.
Uptech tip: Ensure that the deployment environment is similar to the training environment to avoid any surprises.
How We Created AI-powered App – Dyvo.ai
At Uptech, we created Dyvo.ai – an AI-powered app that allows users to create personalized avatars in no time. One of the biggest challenges we faced in building Dyvo.ai was developing an app that would generate AI images that users would like.
We had to learn how to apply Stable Diffusion technology in its best shape, so it’d allow us to:
- Create images similar to the people depicted in the original photos;
- Avoid artifacts and other bugs associated with AI;
- Generate images that users will like (the most significant challenge).
To overcome this challenge, we conducted a lot of experiments with training models, prompts, and configs (sampling methods, steps, CFG scale, X/Y plotting, and seeds).
That way, we ensured that the users would get the AI-generated images that were the most similar to them while saving our time.
Another challenge we faced was optimizing app development costs. Conducting all those experiments takes lots of time and money. To rent one GPU – a graphics processing unit that processes the images, costs around $300-400 per month. It was not cost-effective considering the price of generating avatars.
To solve this money challenge, we searched for other options and found runpod.io – a service that allows renting cloud GPUs on an hourly base. Now we can rent the GPUs only when we need them. It was a winning decision and saved us a significant amount of money.
Overall, the development of Dyvo.ai was a challenging but rewarding experience. We learned a lot about AI software development, and we are proud to have created a platform that allows users to create top-quality AI-powered avatars in no time. For more details on Dyvo.ai development and features, check out our case study.
3 Non-cliche AI Software Ideas
Before the question “how to build AI software?” always comes “what AI software to build?” I know firsthand that coming up with app ideas is a challenge. So if you’re looking to build an AI-powered startup but not sure where to start, here are some non-cliché ideas that can inspire your own project:
- AI-powered personalized nutrition app: Nutrition is highly personal, and AI can help personalize it further. An AI-powered app can collect data on your health, lifestyle, and preferences and suggest a personalized meal plan that meets your nutritional needs.
- AI-powered financial planning and investment app: Fintech niche is quite promising. You can benefit from it by using machine learning to provide personalized investment advice through the app.
- AI-powered event planning app: Planning events can be a daunting task, but AI can help simplify it. An AI-powered app can recommend venues, caterers, and vendors based on your preferences and budget. It can also help you create a timeline, send invitations, and manage RSVPs.
The Future of AI Software Development
Artificial intelligence is already transforming the way we live and work, and this trend is only going to accelerate in the future. According to a report by Grand View Research, the global AI market is expected to grow by 37.3% from 2023 to 2030 and reach 1,811 billion. The report also predicts that the healthcare and finance industries will be major drivers of AI adoption in the coming years.
AI technology is advancing rapidly, with new developments in machine learning, NLP, and computer vision. As AI technology continues to improve, we can expect to see more sophisticated and powerful AI software that can tackle even more complex problems.
Building AI software can be a complex and challenging process, but with the right approach and expertise, it can lead to transformative results. Whether you're looking to build an AI-powered startup or integrate AI into an existing product, Uptech is here to help.
Contact us today to learn more about our AI software development services and how we can help bring your ideas to life. Remember, building AI software is all about understanding how to build AI software!
How to build AI software?
Follow these 6 steps:
1. Identify the business problem you want to solve with AI
2. Gather data
3. Choose an AI technology you want to use
4. Build and train the model
5. Test the model
6. Deploy the model
How much does it cost to build AI software?
The cost of developing AI software depends on the app's complexity, the technologies used, the team engaged, and the outsourcing partner's location. At Uptech, we offer several options:
1. Developing AI app from scratch and starting with the MVP;
2. Rebuilding the existing app and extending the feature base;
3. Polish the existing app by improving some parts of the app. On average, it takes us 3 - 5 months to develop a functioning MVP. In 3 months you'll have a bare minimum product with the basic set of features to attract your early adopters and validate a product idea. To develop the fully-functional app, you'll need the project team, which includes:
- Project manager
- UX designer
- Back-end developers
- Front-end developer
- QA engineers This is the general scenario. To get the precise numbers of how much it may cost to build AI software, contact our team. We'll help you with the numbers and answer the related questions.