How This AI Note Taker Makes Up To $300K/Mo

+ AI Tools that will help you replicate its results.

Hi!

A couple of weeks ago, we discussed how AI Calorie Trackers are making inroads in social media and using their advantages to gain consumer trust (that post is here). The other day, I came across another category of AI apps that are also gaining momentum: Note-Taker Apps.

These are also a pretty popular startup type among creators; and there's much to learn from them. Both in terms of product creation and strategy and terms of viral marketing. Today, let's break down one case study (which grew to $300K MRR), discuss why it's hitting its target audience, and take tools to achieve similar results.

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AI Note Taker Apps

To avoid wasting time on a typical explanation of this category of apps, I propose to look at such products from three perspectives: business, developer, and consumer. Next, we will also look at a specific example, but for now, you can keep in mind that there are dozens of similar solutions on the market, some of which offer minor differences in functionality and design.

Business Perspective

From a business perspective, AI-powered note-taking apps are part of a broader productivity software space that is growing but also competitive. These apps typically use AI to summarize meetings and create to-do lists. Many creators use AI wrappers to launch such apps and quickly generate revenue.

We talked more about AI wrappers in this post:

Quick Start Guide for AI Wrapper

In terms of revenue model, most of these apps follow a standard SaaS approach, offering tiered subscription plans (free for primary users, paid tiers with additional features like real-time transcription or integration). It's a common model, and it's pretty hard to stand out unless the creator offers unique features.

The demand for AI note-takers is relatively high because of the broad audience: they can be both regular users and enterprise-level customers who need to share information with colleagues frequently and quickly. Depending on the choice, the monetization model can differ markedly.

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Developer's Perspective

Developers create such apps relying heavily on natural language processing models for transcription, abstracting, and organization. Typically, the choice falls on GPT-4, which is quite affordable and the most advanced LLM in this matter. A powerful natural language processing pipeline is crucial. The developer needs to think about how the app handles different accents, languages, or terminology.

The latter is especially important for specialized industries like finance and law.

Customers Perspective

From a user perspective, AI-powered note-taking apps are just another tool to help automate tasks like taking notes during meetings or writing resumes. The average user wants something simple, nothing too complicated. If the interface is clunky or the app complicates things too much, they will quickly give up on it.

For some users, integration is also important because they won't use these apps in isolation. So AI note-takers need to integrate well with other tools they already use - calendars, email, Slack, etc. - otherwise, they're just another tool to manage.

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Here are a few examples of such apps:

• Reflect

• Krisp

• Granola

• Taskade

• Coconote

Now let's break down the last app on this list. Coconote stands out from other solutions with several achievements at once. Not only has this app managed to reach an impressive $300K per month, but it has also reached over 80M views on social media and received over 10M likes.

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How Coconote AI Note Taker achieved a $300K MRR