Fello AI REVIEW One Native Apple App for ChatGPT, Claude, Gemini & More

Explore how Fello AI combines today’s leading AI models into a single native app for macOS, iPhone, and iPad, offering seamless model switching, document analysis, image generation, and cross-device syncing.

I have to admit that when AI first became the latest buzzword, I was hesitant to embrace it. It wasn’t that I had anything against the technology, but I was skeptical of the hype surrounding it. Once I started using ChatGPT regularly and learned how to craft effective prompts, my perspective changed. AI quickly became part of my daily workflow, helping with everything from brainstorming ideas to editing and research.

As useful as AI has become, one challenge has only grown over time: the sheer number of large language models (LLMs) available. Some excel at writing, others are better at coding, research, or reasoning. Knowing which model is best for a particular task isn’t always obvious, and managing multiple apps or subscriptions can quickly become frustrating. Over the past year, I’ve found myself reaching for different models depending on the task at hand. GPT might be my first choice for one project, while Claude or Gemini might be better suited for another.

I’ve also found that many third-party AI interfaces require you to supply your own API keys. Not only does that add another layer of setup, but it also means managing API usage and, in many cases, paying separately for access to each provider. That’s one of the reasons Fello AI immediately caught my attention. Instead of asking users to bring their own API keys, it includes access to a wide selection of AI models through a single subscription. Combined with its native Apple experience, that makes it an appealing option for anyone who wants the flexibility of multiple AI models without the extra complexity.

What Is Fello AI?

Fello AI is an all-in-one AI assistant designed specifically for Apple’s ecosystem, bringing many of today’s leading large language models (LLMs) together in a single native app for Mac, iPhone, and iPad. Rather than requiring users to subscribe to and switch between separate AI services, Fello AI aims to provide one centralized workspace where users can access multiple models for writing, research, coding, creative projects, and everyday productivity.

According to the developer, future updates will continue expanding these semi-agentic capabilities, enabling Fello AI to interact with additional file types and third-party applications so it can complete tasks instead of simply responding to prompts.

Built from a Personal Need

Originally released in April 2024, Fello AI began life as a simple ChatGPT client for macOS. Its creator built the app after becoming frustrated with the web experience and wanting a faster, more reliable native alternative. As more users discovered the app, they requested support for additional AI models, image generation, document creation, and other productivity features. Those requests ultimately shaped Fello AI into the comprehensive AI platform it is today.

Since its initial release, the app has received 124 updates, reflecting an active development cycle driven largely by community feedback rather than infrequent major releases.

Designed for Apple Users

Fello AI is available for Mac, iPhone, and iPad with real-time synchronization between devices. Built using Apple’s latest development technologies and design guidelines, the app delivers a consistent native experience across each platform.

New users can get started with a free tier that includes limited daily access to premium AI models along with unlimited conversations using supported free models. Those who want unrestricted access to all available models and features can subscribe through a monthly or annual plan, both of which include a free trial. The developer also notes that the app contains no advertisements or hidden fees.

Privacy and Customer Support

Privacy is a major focus for Fello AI. The app does not require users to register before getting started, and the developer says it does not collect analytics or use customer data for advertising purposes. They have also opted out of AI model training wherever supported by the underlying providers. When cloud storage is needed for synchronization or saved content, data is managed through Firebase and Google Cloud using standard security practices.

Customer support is intentionally personal as well. Rather than routing users through a large support team, the developer handles support directly and says user feedback plays a significant role in determining which features and improvements are added to the app. They also strive to respond quickly, often within an hour of receiving an email.

Looking Ahead

Development of Fello AI continues at a rapid pace. According to the developer, upcoming features include Projects, which will allow multiple conversations to share context within dedicated workspaces, and voice chat for hands-free AI interactions.

The team is also planning major enhancements to its recently introduced Skills feature, which is designed to let Fello AI connect with both local and online third-party applications so it can automate tasks instead of simply generating responses. Alongside these additions, the developer says they will continue adding new AI models while improving the app’s speed, responsiveness, and overall user experience.

Those ongoing improvements appear to resonate with users. Fello AI currently maintains a 4.7 out of 5 worldwide rating, and according to the developer, every update is shaped by real customer feedback, a philosophy that continues to guide the app’s evolution.

Pricing & Availability

Fello AI offers a free tier that lets users explore the app before committing to a subscription. According to the developer, the free version includes limited daily access to premium AI models along with unlimited conversations using supported free models. A free trial is also available for users who want to test the app’s full feature set.

The App Store currently lists several subscription options, including weekly, monthly, quarterly, and annual plans. Pricing varies depending on the plan selected and may reflect both current and legacy subscription offerings:

The developer states that a subscription unlocks access to all supported AI models and premium features without advertisements or hidden fees. Compared to maintaining separate subscriptions for multiple AI services, Fello AI’s all-in-one approach may offer a more economical option for users who regularly switch between different AI models.

User Experience

Getting the app set up to use is very easy. You simply state what you mainly use AI for, walk through the short tutorial of what AI can be used for, agree to the Third-party AI Processing terms, and then you get started with a chat. I actually started with the macOS version of the app and then installed the iOS version. I was able to restore the purchases (subscription) to the iOS version that I was using on the Mac, but I noticed the chats weren’t present until I logged into Fello AI with my Apple email (you can also log in with a Google account). Once the two were synced, they stayed in sync and are very quick to update.

The design is very similar to what you see with ChatGPT’s iOS and macOS apps. It’s a clean interface and it’s very easy to navigate. The chats and projects are located in the sidebar and you can switch between your different chats with just a click. It would be nice if there were other UI options and different colors or themes to choose from, but it’s very easy to read as it is.

Working with Multiple AI Models

One of the first things I noticed while using Fello AI is how easy it makes switching between AI models. Rather than forcing you to start a new conversation each time you want to try a different model, the app includes a simple drop-down menu in the upper-right corner that lets you switch models whenever you like, even in the middle of an existing conversation.

At the time of testing, Fello AI offered access to 13 standard language models, 12 reasoning models (with some overlap between the two categories), and five image generation models. Switching between them was nearly instantaneous. Simply select a different model, submit your next prompt, and the conversation continues.

To see how well this worked in practice, I started a conversation with GPT 5.6 about the history of banana bread. After the model finished its response, it suggested a follow-up question about how the recipe has evolved over time. Rather than continuing with GPT, I switched to Claude 5 and simply replied, “Yes, please explain how the recipe has changed over time.” Claude immediately picked up the conversation and generated a thoughtful response without requiring me to repeat any context. The only difference I noticed was that Claude’s response took slightly longer to generate than GPT 5.6’s, though the delay was minor.

I also used the same prompt across several models, asking each to write a 500-word introduction for Banana Bread History. GPT, Claude, Gemini, and DeepSeek all generated responses quickly, but each had its own writing style and structure. Instead of trying to determine which model was “best,” I appreciated being able to compare their approaches without leaving the app.

Everyday Writing

Since much of my day revolves around creating content, I spent a considerable amount of time using Fello AI for everyday writing tasks. Using GPT 5.6, I asked it to create a press release, an SEO title, a meta description, a social media post, and an email draft centered around banana bread.

Every request was completed quickly, and the formatting was clean and easy to work with. The generated content required very little cleanup before it was ready to use. The email draft was particularly impressive because it felt conversational and engaging rather than sounding overly robotic. While every AI model has its own writing style, Fello AI made it easy to move between them depending on the type of content I wanted to create.

Research and Document Analysis

Fello AI also proved to be a capable research assistant. To test its document analysis capabilities, I uploaded a PDF containing a banana bread recipe from UC Davis Health and asked it to summarize the document, create a list of frequently asked questions, and explain the recipe in plain English.

Fello AI produced exactly the kind of information I was hoping to see. The summary accurately highlighted the most important details without becoming overly verbose. The generated FAQs covered practical questions that someone following the recipe would likely ask, including storage recommendations, freezing instructions, serving suggestions, baking time, and ingredient preparation. The plain English explanation simplified the baking process into clear, easy-to-follow steps while preserving the recipe’s key details. Overall, I was impressed with how well Fello AI understood the document and transformed it into several different formats without losing important information.

Image Generation

Image generation was another area where Fello AI performed well. Using the Nano Banana image model, I first asked it to create an image of banana bread sitting in a warm, rustic kitchen with a window overlooking a colorful fall landscape. The generated image closely matched my prompt and looked polished enough to use in marketing materials.

From there, I continued refining the concept by asking the model to create marketing graphics, desktop wallpapers, product mockups, and application icons based on the original image. Each request completed quickly, and the results consistently maintained a high level of quality.

Fello AI doesn’t currently offer an extensive set of built-in image editing tools. Instead, refinement happens naturally through follow-up prompts or by regenerating an image. While more editing controls would certainly be welcome, I found the conversational workflow to be simple and effective.

Projects and Organization

Projects were available in the version I tested and proved to be an effective way to organize conversations. Creating a new project was straightforward. The app prompted me to provide context and instructions for the project, giving the AI additional background before any conversations began.

I also appreciated the ability to move existing chats into a project, making it easy to organize ongoing work instead of starting over. For anyone juggling multiple writing assignments, research projects, or personal conversations, Projects provide a clean way to keep related discussions grouped together and maintain context over time. I can see this being especially useful for keeping separate conversations for work, personal use, and long-term writing projects without having unrelated chats mixed together.

Conclusion

Fello AI impressed me by delivering exactly what it promises: a native Apple application that makes it easy to work with multiple AI models from a single interface. Rather than juggling separate apps, subscriptions, or API keys, I was able to switch between leading language models with just a few clicks while keeping my conversations organized and synchronized across my devices.

If you’re invested in Apple’s ecosystem and regularly use multiple AI models, Fello AI is an excellent solution that removes much of the complexity associated with today’s AI landscape. It provides a polished experience that feels at home on macOS, iPhone, and iPad while continuing to evolve through frequent updates and active developer support.

For more information, visit felloai.com