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Paul Yacoubian
Home  >  Companies  > is a generative AI copywriting and marketing tool.




Growth Rate (y/y)








Note: All data as per publicly available information hit $10M ARR in October 2022—up 346% from last year—growing at a rate of about 20% MoM since July. We expect to hit about $11.6M by the end of 2022.’s revenue comes primarily from subscriptions to their writing tools, with pricing based on number of words generated. has free and pro tiers, with the pro tier including access to 5 user seats, priority customer support, and support for 25+ languages.

Business Model

None is an AI-assisted copywriting app built on top of OpenAI’s foundational GPT-3 model.

Content marketers, social media managers, and email marketers use to generate copy for Facebook/Google ads, blog posts, Twitter threads, and more.

Initially, began as essentially a wrapper around raw GPT-3. Today, has 20-30 distinct fine-tuned models that operate on different parts of the content generation process. uses data about how users engage with the outputs of their models—whether they save, edit, rewrite, or otherwise change what came out of—in order to iterate on those models and improve the quality of their output.’s biggest cost center (after salaries) is paying for access to OpenAI's models, load balancing, and compute facilities they rely on. pays OpenAI a fee every time a user generates a new word, putting a cap on margin expansion at scale.

OpenAI charges 6X more for API calls to fine-tuned models compared with vanilla GPT-3 API calls, so while operates with a typical SaaS gross margin of 50%+, those margins may come under pressure over the long-term.'s pricing model decreases per word cost as users generate more words, incentivizing them to expand usage. At the same time, gets the upside of making more money and more data to feed into fine-tuned models, improving their output.


None is a web app that allows users to quickly generate and iterate on AI-created content for websites, ads, and social media copy. found initial product-market fit with freelancers from platforms like Upwork and Fiverr that used it to quickly generate blog posts and other deliverables which they could then re-sell on those marketplaces with a markup.

Independent contractors using like this tended to come from lower income countries where English isn’t spoken, allowing them to execute on a kind of geographical, AI-assisted labor arbitrage when working with clients in the United States and Western Europe.

Today, is used primarily by marketing teams and SMBs to help them create content for their websites and social channels more quickly.


None operates in a crowded market. ~50 text processing and ~25 image processing generative AI startups have launched in the last 12 to 18 months, most of them using foundational AI models from OpenAI ($20B) and Stability AI ($1B). Large tech incumbents like Microsoft and Google, with proprietary foundational AI models, are also integrating AI in their apps.

Generative AI startups

OpenAI and Stability AI are arming startups to build generative AI apps by letting them cheaply rent foundational AI models that rival Google and Microsoft’s models in scale.

At the same time, they are also commoditizing the application layer by making it cheap and frictionless for anyone who can code to launch generative AI apps. This gives them enough leverage to create a redux of the smartphone era, where the fat layer of iOS and Android platforms captured the bulk of the value.

However, unlike during the smartphone era, the foundational layer incumbents like OpenAI risk becoming redundant with the emergence of free, open-source language models like BLOOM that are as large as GPT-3. In August 2022, OpenAI slashed the price of vanilla GPT-3 by two-thirds, making it even cheaper for developers to test it out rather than rely on free, open-source models.

Large tech incumbents

Among the incumbents, Microsoft and Google have the biggest opportunities, given their proprietary foundational models and billions of existing software users/customers. Unlike startups, they don’t have to pay the OpenAI tax and can bundle AI assistants for near-free in their apps by spreading the model’s cost over billions of users. Microsoft’s foundational model MT-NLG has 530B parameters, and Google’s PaLM has 540B parameters, making them strong competitors to GPT-3 with 175B parameters.

TAM Expansion

Horizontal expansion started off with a simple tool—a language model, trained on Wikipedia entries, designed to help marketers create copy for any product and for any audience in seconds.

Since then, they’ve launched 90+ AI tools, including generators for sales copy, ad copy, social posts, resignation letters, real estate listings, cold emails, job descriptions, and more.

While’s core customer base today revolves around marketing teams and SMBs, there’s an opportunity for them to expand across the organization as they eat up other use cases outside content writing and social media marketing—for example, creating collateral for and helping with basic outbound and inbound sales tasks.

Enterprise sales motion

Today,’s core customer base is SMBs—but they have an opportunity to drastically grow their ARPU and net dollar retention by moving upmarket into the enterprise.

In SaaS at scale, enterprise growth tends to outpace SMB growth and ultimately represent a huge and growing portion of revenue.

One advantage for is that as with a tool like Canva, the relevant workflow across SMBs and enterprises is relatively similar. Unlike a product like Brex where SMBs and enterprises fundamentally use the product in different ways, teams using to create content have the same core needs whether they’re in big or small companies.

To make this move upmarket, will likely need to implement key prerequisite features like SSO and SOC-2 compliance, alongside things like team collaboration, brand controls, reporting, and asset management.


Low switching costs competes with AI-based copywriting products from companies like Jasper, Writesonic, Copysmith, Clickable, Ponzu, Simplified, and others.

And with products like Github Copilot and Microsoft’s new AI art generator, we’re already seeing how the biggest tech incumbents are looking to embed generative AI into their existing products.

Today, there isn’t any specific proprietary technology or network effects that differentiate from these different players—e.g. any factors that would make it harder for users to simply switch over to another platform.

Long-term unit economics

Once the generative AI startups move beyond early adopters, their relative lack of differentiation may force them to invest more in growth via more paid ad campaigns, bumping up CAC and putting pressure on their unit economics.




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