AI wrappers are a controversial topic in the tech industry.

While many people (ehm haters) are saying AI wrappers aren't real businesses and mocking makers building them, the makers are laughing at them and reaping the benefits.

PDF.ai makes a cool $60k+ MRR.
Photo AI does over $75k MRR.
And Rezi crossed $220k MRR.

No pocket money at all huh?

What is an AI wrapper in the first place?

AI wrapper, or GPT wrapper, is a tool that provides users with an interface to input some data (text, photo, video, PDF, CSV file), sends this input to the API of the AI model (like GPT-4, Claude, Llama, or Stable Diffusion) with instructions (e.g. get insights from the PDF, generate text or image), and returns the output to the user.

AI wrappers usually serve a single purpose and allow users to achieve it with minimal effort.

This low level of complexity allows solo developers to quickly build and launch them without needing a large team.

Haters would say "but it's just a bunch of API calls stuck together".

Maybe. Maybe not.

But your users don't care if your product is an AI wrapper or not. They only care that it solves their problem. And if the pain point is big enough, they will gladly pay for your product to solve it.

Profitable AI wrapper examples

Below are a couple of successful SaaS products that started as simple AI wrappers.

As they grew, their features got more complex too, so it would be insulting to call them AI wrappers at this point.

Notice how each of them is kind of a niche version of ChatGPT built for a very specific use case or audience.

PDF.ai

Revenue: $60k+ MRR (source)

PDF.ai lets you "chat" with your PDF documents as you'd chat with ChatGPT - using natural language.

The AI tool sends the uploaded PDFs to an LLM which "reads" them, processes users' questions, and returns answers based on the document's content, saving users tons of time and effort.

PDF.ai is run by Damon Chen, a prolific maker, who acquired the initial product while it was still at the MVP stage, rebranded it, and grew to over $60k in MRR.

Chatbase

Revenue: $335k+ MRR (source)

Chatbase lets developers create custom chatbots based on their data. This allows companies to respond to website visitors based on brand-specific knowledge using the brand's tone of voice.

You could call it a ChatGPT wrapper that's fine-tuned based on user data and instructed to reply in a certain way.

The founder, Yasser Elsaid, grew Chatbase mostly using word of mouth. He builds the company in public by posting regular updates on Twitter/X and benefited from a first-mover advantage as Chatbase's capabilities were a wow factor making his demo tweets go viral.

TypingMind

Revenue: $45k+ monthly revenue (source)

Built by a Vietnamese indie hacker Tony Dinh, TypingMind is a better user interface for ChatGPT, Gemini, Claude, and other AI models, all accessible from one chat interface.

Unlike the previously mentioned AI wrappers, TypingMind is available as a one-time purchase and users need to bring their own API keys. This keeps Tony's bills very low.

TypingMind also provides custom AI agents trained on their users' data which is targeted at enterprise customers. This offer helps bring in huge deals like this one:

Tony grew the tool to over $45k monthly revenue mostly by building in public on Twitter/X.

SiteGPT

Revenue: $11k+ MRR (source)

Similar to Chatbase, SiteGPT is a website chatbot trained on customers' websites and knowledge base content that provides visitors with factual, on-brand responses 24/7.

The quality of responses keeps getting higher the more data is fed into the tool. This is achieved by continuously fine-tuning the underlying OpenAI model based on data from third-party sources.

SiteGPT was built by Bhanu Teja who sold his previous SaaS for $250k.

Julius AI

Revenue: undisclosed, 500k+ users (source)

Julius is an "AI Data Scientist" used for analyzing and visualizing large datasets and training AI models.

ts would be a huge understatement as it's capabilities are much higher than what ChatGPT can do.

Julius was backed by YCombinator in 2022.

How to build an AI wrapper

If you've decided to build an AI wrapper, here's how you can get started (and hopefully replicate the success of the products mentioned above).

1. Pick an idea

Ideally, it should be something that you can build the MVP quickly (considering how quickly the landscape changes) and that has a proven demand.

Examples of such ideas in the next section.

Of course, knowing the niche and audience well gives you a big advantage.

2. Come up with a distribution strategy

Yes, you should do it before starting to build your product. If you have no idea of how to reach your target audience, it's going to be tough to get it off the ground.

You should at least know how to reach an initial batch of users to validate your AI startup idea.

3. Build the MVP

And finally, the fun part - building the MVP of your AI wrapper.

The best way to do it is to use an AI SaaS boilerplate which will save you tons of time on coding the repetitive stuff like authentication, database, payments, emails, UI, and more.

Instead, focus on building features that add value to your product.

Recommended boilerplates in a later section.

Next, when your MVP is ready, you can launch it, get feedback from users, keep improving the product based on their feedback, and scale it.

Thin vs thick AI wrappers

Not all AI wrappers are created equal though.

Most of them would be classified as "thin wrappers". Those that just accept the user input, send a simple request to the API and return an average-quality result. Most of their value comes from the underlying LLM and the wrapper provides very little extra.

Thick wrappers, on the other hand, produce much more valuable outcomes thanks to using one or more of the strategies below:

• Prompt engineering - using more sophisticated prompts to improve the output quality
• Customizing user experience to a specific use case and/or audience
• Post-processing - refining the API responses to meet certain requirements
• Chaining multiple AI models together to handle complex use cases
• Using proprietary data to give the AI model more context which results in personalized outputs (like AI assistants do)
• Third-party integrations
• Fine-tuning the AI model for a specific use case The key thing to remember is that thin wrappers have no moat. If the only added value in your AI wrapper is a user interface, anyone can reverse-engineer your prompt and copy your product in no time.

Does it mean you can't build a profitable thin wrapper AI startup?

No. As with any software, the key is distribution. So if you know how to market your AI wrapper, you can create a fairly successful business even without a moat.

After acquiring first paying users and validating your product idea, you should build a moat to sustainably grow the product in the long term.

AI wrapper startup ideas

But first, you need an idea.

Here's a list of AI wrapper ideas with proven demand (based on search volume) that are on the rise and also easy to rank for in search engines.

AI tattoo generator

Estimated search volume: 14,800/month
Keyword difficulty: 28/100

Create a tattoo generator app to help people who have a general idea of what tattoo they want but need help visualizing the final design.

Users would provide a description of the tattoo's theme and style (and optionally a reference design), and the generator would create multiple suggestions of design for inspiration.

As an extra value-add, you could add a feature allowing users to visualize how the tattoo would look on their skin.

This app would also be a great fit for tattoo studios as a lead generation tool to attract potential clients.

Use Stable Diffusion or Flux to build this AI wrapper.

AI lyrics generator

Estimated search volume: 8,100/month
Keyword difficulty: 27/100

Help aspiring songwriters speed up their creative workflow by building an app that writes song lyrics based on user-defined genre, theme, mood, or even a few starting lines.

Then, let users regenerate portions of the lyrics or tweak certain parameters to refine the output.

You can create this app as a wrapper around any of the major large language models such as GPT-4, Claude, Llama, or Gemini.

AI signature generator

Estimated search volume: 2,900/month
Keyword difficulty: 15/100

Use a text-to-image AI API like Flux or Stable Diffusion to let users create unique, personalized digital signatures based on their desired style and complexity

Some potential uses for AI-generated signatures include digital document signing, email signatures, personal branding, or adding a personal touch to digital art or designs.

Baby AI generator

Estimated search volume: 8,100/month
Keyword difficulty: 24/100

Build this app for people wondering what their baby will look like.

Let parents upload their images and select the gender of the baby Then, your AI wrapper would analyze parents' facial features to create a unique, photorealistic image of what their baby might look like based on the given parameters.

Shopify AI website builder

Estimated search volume: 2,400/month
Keyword difficulty: 29/100

Help beginner ecommerce store owners speed up the process of building their Shopify store using an AI-powered website builder.

Users would provide details about their brand such as the type of products they sell, their target audience, and their brand style preferences, and the software would handle the rest. Ideally, everything from website design and color scheme to content generation, search engine optimization, and applying ecommerce conversion rate best practices.

Of course, let users customize the AI's suggestions before creating the final design.

While this is not the easiest AI wrapper idea to build, the value users would get is big. Imagine how much money it would save them compared to hiring a full-service development agency.

AI album cover generator

Estimated search volume: 1,900/month
Keyword difficulty: 16/100

Create an AI wrapper that helps generate unique album cover artwork for musicians without requiring any design skills.

This is a relatively easy product to build with a huge market.

Use Flux or Stable Diffusion as image generation APIs.

AI landscape generator

Estimated search volume: 1,000/month
Keyword difficulty: 18/100

Another text-to-image or image-to-image AI wrapper idea is a generator of realistic-looking landscapes that could be targeted at architects, urban planners, or real estate agents.

It could generate both landscapes from scratch as well as edit existing ones based on user-defined criteria such as vegetation style, terrain type, time of day, or weather conditions.

AI reference finder

Estimated search volume: 720/month
Keyword difficulty: 15/100

If you'd like to target academics, researchers, and journalists, an AI reference finder tool is an interesting AI wrapper idea with growing demand and low competition.

Finding, organizing, and formatting references is very time-consuming and your product could make this process less burdensome.

Users would provide details about the topic they're researching (or details of a specific citation they need) and the AI reference finder would identify the sources based on checking relevant databases of academic papers, books, articles, and other sources.

AI contract generator

Estimated search volume: 590/month
Keyword difficulty: 19/100

This AI wrapper idea could save companies thousands on legal fees.

Users would provide key information about the contract, such as the type of agreement (e.g., employment, non-disclosure, sales), parties involved, and specific terms or conditions they need to be included, and the AI API would prepare an agreement draft for them to approve.

In case of complex or unique contractual situations, having a legal professional review the final version of the agreement would be recommended though. For this part, you could partner with a law firm on a revenue-share basis.

UI generator AI

Estimated search volume: 880/month
Keyword difficulty: 25/100

Create an AI-based UI (user interface) generator to let designers and non-technical founders quickly create prototypes of web and mobile apps, as well as websites.

Users would describe the product, features, and style they want in their UI, and your product would generate a prototype based on that. An extra feature would be generating the UI based on a reference screenshot of another design users would like to get inspiration from.

It's not the easiest AI wrapper to build but the value (and time savings) for users would be big.

AI starter kit and boilerplate list

Ok, so how do you ship your AI wrapper in record time?

The answer is AI SaaS starter kits (also known as AI SaaS boilerplates).

While you could build everything from scratch, it's not worth your time if you can use a boilerplate with all the SaaS essentials set up for you.

Here's a list of the best boilerplates to build your AI wrapper.

AnotherWrapper

AnotherWrapper is an AI starter kit for building AI wrappers at lightning speed. Aside from a complete SaaS infrastructure, it includes integrations with OpenAI (GPT-3, GPT-4, GPT-4o, DALL·E 2 & 3, Whisper), Anthropic, Replicate, Groq, and LangChain.

And if that's not enough, you can start with any of the 10 customizable AI demo applications to build your AI wrapper 10x faster.

WrapFast

WrapFast is a SwiftUI boilerplate that has everything you need to build monetizable AI wrappers and iOS apps fast.

It includes pre-built modules for user authentication, onboarding, in-app purchases, paywalls, and a cloud database via Firestore. It has endpoints for OpenAI and Anthropic Claude and secures your (or your users') API keys with a Node.js Express backend.

WrapFast also has detailed documentation and step-by-step tutorials to get you set up. Lifetime updates and a private Discord community for support are included.

Gravity

Gravity has a pre-configured Node.js and React setup so you can build market ready SaaS apps fast.
Key features include a robust subscription billing system with Stripe, multi dimensional auth with 500+ social networks, 50+ React components for accessibility and dark mode. Choose from 10 databases and a fast REST API with token auth. User management with role based access, transactional emails, localization and an admin dashboard to manage your business.

Lifetime support, continuous updates and a community driven roadmap.

NextStarterAI

NextStarterAI is a Next.js template to build AI wrappers and SaaS products fast thanks to Replicate and OpenAI integrations and Runpod deployments out of the box.

It also comes with a full SaaS setup including Tailwind CSS for styling, Supabase for user authentication, integrated payment systems like Stripe and Lemon Squeezy, waitlist feature, and even a complete blog framework.

NextStarterAI is highly customizable to save you time on setting up tasks like API configurations and customer support integrations.

BuilderKit

BuilderKit is a modular NextJS AI boilerplate that supports major AI models and workflows like GPT-4, Claude, Llama, Mistral, Whisper, and Deepgram.

There are modules for all the most common use cases such as text generation, image generation, speech-to-text, and text-to-speech. It also has 14 pre-built AI apps and all the fundamentals of building a SaaS product such as Stripe and Lemon Squeezy payments, Supabase authentication, Loops email services, server-side rendering, edge functions, landing pages, waitlist pages, admin dashboard, and much more.

BuilderKit has all you need to get you up and running with production-ready AI wrappers (and not only).

NuxtStarterAI

NuxtStarterAI is a SaaS and AI wrapper boilerplate made by the makers of NextStarterAI. It has all the same features but is built with Nuxt developers in mind. It lets you ship apps using Replicate and OpenAI APIs and deploy them on Runpod's globally distributed GPU cloud.

And also build your AI wrapper using modular components such as canvas, prompt inputs, animated tabs, and more.

HorizonUI

Horizon UI is an AI wrapper boilerplate for React and Next.js apps and websites. With production-ready templates, 100+ components and elements, and 33 fully-coded example pages, using Horizon UI as a starting point for your next AI SaaS is a huge time-saver.

Boilercode

Boilercode has NextJs and React boilerplates for SaaS product development.

Features include user authentication with social login and magic link, Stripe and LemonSqueezy payment integration, configurable SEO files, email integration, landing page creation, Crisp customer support, OpenAI and Dalle-3 image generation, database setup, webhook for subscriptions, LangChain for natural language processing, Pinecone for vector search and PDF chat.

All these save developers time on setting up databases, checkout processes, custom blogs and more.

AI & SaaS Template

The AI SaaS Template is a full-stack Django boilerplate to help you build your AI wrapper in record time.

It not only has customizable OpenAI-based app templates but also easy-to-follow guides to help you create your own AI app in hours. It comes with preconfigured integrations for user authentication (django-allauth), payment processing (Stripe), email services (Mailgun), and Heroku deployment. It also has both Tailwind CSS and Bootstrap options for a modern responsive UI. Detailed documentation, step-by-step tutorials, and AI app templates are included so even a basic Django developer can get up and running quickly.

Created by Leon Wei who shipped 20+ products with Django in the last couple of years.

DeployFast

DeployFast is a one-click solution to deploy AI wrappers with FastAPI, Docker, and Streamlit with OpenAI and ElevenLabs APIs.

It provides ready-to-use API calls for JSON mode chat completion, image generation, speech-to-text, and text-to-speech. All you need is to add your API key. You can also create your own customized API endpoints with automatic documentation, and deploy them with Docker to your favorite cloud provider.

DeployFast is also easily containerized for any cloud (AWS or Azure), which makes the setup and deployment easy for both newbies and pros, so you can focus on building AI wrappers and applications quickly instead of worrying about the infrastructure.

ShipGPT

ShipGPT is a complete Next.js AI app boilerplate made for launching AI wrappers and SaaS products easily. It integrates with AI APIs for every possible use case (conversation, audio, video, image), and lets you train your models. ShipGPT supports most major AI model providers such as OpenAI, Google Gemini, Anthropic, Langchain, and Pinecone.

You can easily build AI wrappers such as custom conversational chatbots for documents and videos, speech-to-text, and text-to-speech apps. ShipGPT also includes server-side rendering and automatic static optimization for fast load times and performance out of the box.

The boilerplate was built by an experienced team that created and scaled multiple AI products.

TemplateAI

TemplateAI is a NextJS boilerplate that makes shipping AI wrappers and apps a breeze. You can build text generation-based apps with Groq and Claude, image generation apps using Replicate (using SDXL, Flux, and more), and handle vector search with LangChain and Supabase pgvector. TemplateAI also has pre-built landing page components, dashboard, API routes, Magic Link and Google OAuth user authentication, and of course, Stripe payments to monetize your AI product.

Mobile responsiveness and SEO settings are available out of the box. TemplateAI removes all the repeatable stuff so you can focus on launching your AI wrapper quickly.

StartKit

StartKit is a comprehensive Node.js boilerplate made specifically for building AI apps and wrappers in record time.

Created by prolific makers, Danielle & James Ivings, StartKit includes pre-built REST API routes for common AI model providers such as OpenAI, Anthropic, Groq, and Llama, as well as text embeddings and Retrieval-Augmented Generation (RAG). It also has advanced retries and fallbacks so your AI wrapper will keep running even if primary AI providers are down. StartKit has user authentication, Stripe or Lemon Squeezy payment processing, and a full admin dashboard.

You can also quickly get up to speed with one of the fully functional and extendable demo apps.

What model to use in your AI wrapper

The AI model you should pick depends mainly on your use case. Here are the most popular generative models that have public APIs available:

• Text-to-text generation: GPT-4, Claude, Llama, Gemini
• Text-to-image and image-to-image generation: Stable Diffusion, Flux, DALL-E
• Image-to-video generation: Stable Video Diffusion
• Text-to-speech generation: OpenAI TTS
• Speech-to-text generation: Whisper Don't spend too much time picking the perfect AI model at the MVP stage though. Just pick one of the major models that does the job well.

After all, there are over 80 large-scale AI models on the market, and thousands more smaller, fine-tuned models and LoRAs (Hugging Face and Civitai are the AI model rabbit holes). You could spend days researching them alone.

Only after your product idea is properly validated, you can find the API that will provide the highest quality-to-cost ratio.

Final thoughts on AI wrappers

Hopefully, this guide gave you an idea of how to launch your first AI wrapper that you'll be able to call an AI company one day.

In most industries, the adoption rate of AI is still at a very early stage so there's a ton of opportunity for disruption. It's up for grabs for indie makers like you.

And remember, it doesn't matter if your startup is a GPT wrapper or not. The only thing that counts is that the product provides value to users.

Let's build!