How to build an AI app: A step-by-step guide

With the rise of technologies like OpenAI's GPT-4 and Replicate's cloud-hosted models, building an artificial intelligence (AI) app has become easier than ever.

You don't need to have a PhD in machine learning or knowledge of how to set up Kubernetes clusters/Docker containers to deploy production-scale AI applications. Instead, you can leverage these tools and platforms to create your own AI applications.

Examples of AI apps

There are several types of AI apps that you can build:

  • Chatbots
  • Writing tools
  • Generative AI apps
  • Agents / Virtual assistants

We've seen a wave of exciting new AI companies built on Vercel, leveraging tools like Next.js and the Vercel AI SDK:


Runway is an applied AI research company shaping the next era of art, entertainment and human creativity.


Jasper is an AI writer and AI marketing software for enterprise teams. Create blog posts, marketing copy, and AI-generated images, fast.

From legal agreements to financial reports, brings your documents to life. You can ask questions, get summaries, find information, and more.

Jenni is an advanced AI writing helper that accelerates your content production. It assists you in writing everything from academic essays and research papers to high-ranking blog posts, providing an effective solution for overcoming writer's block.


Tome is a new way to express your ideas. Use AI to generate content and images, presentations, landing pages, and more.

Headshot Pro

Headshot Pro is the #1 Professional AI Headshot Generator. Get professional business headshots in minutes with an AI-photographer. Upload photos, pick style & receive 120+ headshots.


Videotap allows you to transform your existing videos into infinite content. Using AI technology, you can repurpose your previously created videos. It's akin to having a squad of content creators slicing and dicing your videos.

This guide will walk you through the process of building an AI app using the latest technologies. Topics covered will include everything from data collection to model training and deployment. You will craft a performant, beautiful AI app without extensive technical expertise.

Step 1: Identifying the problem

Before you dive into building your AI app, ask yourself:

  • What specific issue or task will your AI app address?
  • Who is your target audience, and what are their pain points?
  • How can AI technology effectively solve this problem or enhance the user experience?

Identifying the problem is the foundational step that will guide the rest of your development process.

Step 2: Choosing an AI model

Selecting the right model is crucial for the success of your app. Depending on your use case, you can choose the appropriate pre-trained models from the following providers:


Replicate lets you run machine learning models without needing to understand how machine learning works.

They have a wide variety of AI models for you to choose from and can be integrated into your application in as simple as a few lines of code.


OpenAI offers a variety of models via an API that you can use to build powerful AI-enhanced products.

  • GPT-4: Powerful Large Language Model suitable for building AI chat experiences, language translation systems, and text generation applications.
  • DALL·E: Image Generation Model suitable for creating generative AI art.
  • Whisper: Advanced Speech Recognition Model suitable for developing voice-controlled AI applications and virtual assistants.


Huggingface offers a variety of powerful AI models such as Mistral's Mistral-7B and Meta's Llama-2-7b. These cover use cases like computer vision, natural language processing, etc.


ElevenLabs specializes in audio AI. They offer high-quality pre-made voices, a Voice Design feature that allows you to create unique voices, and two different types of voice cloning features: Instant Voice Cloning and Professional Voice Cloning.

They also recently released the Dubbing feature. This lets you translate your video/audio content into different languages.

Step 3: Building the frontend

Once you have the right model, you'll need to build the frontend for your AI application.

Your frontend is the first impression for your users. Much like how It's important that you use an appropriate model, it's important that you make a good first impression.

Take popular AI products like ChatGPT and Pi for instance – they both have a fast and intuitive user experience.

Pi's chat interface
Pi's chat interface

Here's a good tech stack for building your first AI application:

  • Next.js: is a React framework that gives you building blocks to create web applications. Not only is it used by some of the largest companies in the world, it is actually what both ChatGPT and Pi are built on as well.
  • AI SDK: an open-source library designed to help developers build conversational streaming user interfaces in JavaScript and TypeScript.
  • TailwindCSS: a utility-first CSS framework that makes it easy to rapidly build your UI designs.
  • Vercel: a cloud platform that provides serverless deployment and hosting for your AI app. It offers seamless integration with Next.js and makes it easy to deploy and scale your application.

To help you get started, we built a Next.js AI Chatbot template that uses this stack to create a chat experience with edge streaming.


Step 4: Fine-tuning your model

Off-the-shelf models can get you a solid MVP. To stand out from your competition, you can go the extra mile by fine-tuning your model.

Early tests have shown a fine-tuned version of GPT-3.5 Turbo can match, or even outperform, base GPT-4-level capabilities on certain narrow tasks. 


A fine-tuned model means you won't need to provide as much context to get better model performance. This can save on token usage and allow for faster response times when prompting.

We've written a guide on how to fine-tune LLMs like GPT-3.5 for your reference. You can also fine-tune text-to-image diffusion models using tools like Dreambooth as well.

Step 5 (optional): Monetize your app

You may decide that you want to redeem some of your AI costs. To do this, you could implement monetization via a subscription model, usage-based pricing, etc.

Here are some templates that you can refer to when building out monetization for your app:


AI apps are becoming more prevalent. It's valuable to understand how AI technology works and how you can build your own.

This guide gives you an overview of how you can get started building your own AI applications today.

We're excited to see what you build!

Further Reading

Here are some additional resources for you learn more about building AI applications:

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