analysis Startup Names Through A Y-Combinator Filter

As domain investors, we are in the business of providing names that businesses and organizations will use. Succeeding at that can be a win-win-win situation. We do well, but startup owners are well served by many good name choices in efficient marketplaces. The marketplaces also benefit when there is synergy between the names provided and the names sought.

If there is a disconnect between what domain investors think are good names, and the sort of names that startups desire, no one wins. In that case, startup owners will follow other paths to their name.

No sector is hotter right now than AI. Artificial intelligence is already disrupting how many things are done, and most predict that will continue for many years. We are living through one of the biggest technological disruptions of all time.

Many startups these days are naturally in the artificial intelligence sector, probably a majority of all startups right now. Domain investors are acquiring domain names that they think will have great value for this sector, whether AI-related .com names, terms in the .ai extension, or something else.

In the most recent 12 months, even if we consider only the minority of sales reported on NameBio, there were $5.5 million in .ai extension sales.

But what sort of names are actual startups using these days?

Not Just Another Data Summary

Probably way too often, I have summarized a set of data, providing an overview for readers here on the NamePros Blog. I looked at an extension or niche, and showed the breakdown by type of name, length, pricing, etc. While that seems like an efficient way to get a handle on a topic, is it really? As a student I learned best when I struggled on my own path through a topic, not when someone told me about it.

Sometimes, to truly understand things, it is important to do more than look at a summary compiled through another person’s eyes, and their blind spots and biases, but rather go to the primary data and make your own hypotheses, look for patterns yourself. I ask you in the next section to do exactly that.

Recent Y Combinator Startups

Y Combinator is possibly the best known tech-oriented venture funding vehicle and learning experience. Y Combinator have funded over 4000 startups. Those startups now have a combined valuation of more than $600 billion.

In the past, Y Combinator funded many of the companies that are now widely known brands. For example, AirBnB, Instacart, Stripe, DropBox, CoinBase, Zapier, Reddit, DoorDash, GitLab, OpenSea, Faire, Jeeves and many others.

Y Combinator offer winter and summer groups each year – each program is actually 3 months in length. For this article, let’s concentrate on the current and most recent groups, W24 and S23. There were 261 listed companies the day I looked, 217 from S23 and, at this point, 44 listed from W24.

It is incredibly easy to browse recent companies from the Y Combinator site. Each company has a logo, name, location, one line description, plus a sector summary. Here is a small sampling from current listings.


For example, startup Magic Hour is based in San Francisco, in the current W24 ‘class’, is a consumer content service, is a pretty small team, was founded in 2023, and described as a “Platform for AI video generation.” If you then (at the Y Combinator site) click on the logo for Magic Hour at Y Combinator you will go to their Y Combinator page, that includes the website and domain name. For example, they operate on MagicHour.ai. You can read the full description on any listed company, that includes a bit about their development and the active founders.

So, before reading further, I strongly suggest that you browse through recent Y Combinator startups yourself. To do that, simply go to this link which should automatically set you up with the W24 and S23 classes.

As well as browse through the listings, act as a researcher or journalist, and jot down in bullet points the key aspects that stick out for you.

Things To Look For

Need some help on what to look for? Here are some possibilities:

1. What sectors and niches seem more common?
2. Roughly what fraction are AI-related?
3. Do most seem to be B2B or consumer oriented?
4. What types of names seem most common?
5. If you are interested in logos, what trends do you notice?
6. You may not have the time to look at all of the extended summaries with websites, but view at least a few.
7. What names particularly resonate with you?
8. What business ideas do you find especially interesting?

Don’t feel restricted to these questions, though, or need to consider them at all. The whole point is to browse the names, and see what strikes you as relevant.

Y Combinator Summary

Y Combinator nicely summarize some things for us in the left hand column. For example,

• While there is some global diversity, the strong majority are North American,193 out of 261. This should be a warning flag that it is entirely possible a similar hub of startups in Asia, Europe or Africa might well have different naming conventions. Not only North America, the majority are from the San Francisco area.
• The majority are B2B, business-to-business, with 190 out of 261. I think we sometimes place too much emphasis on consumer facing businesses, so this is a good reminder not to overdo that.
• Each listing can assign various tags, so the total number is much higher than the number of business listings. The most popular tags are B2B, Artificial Intelligence, AI, and SaaS, although things like developer tools, fintech and infrastructure are also common. Note that AI appears under various tags, including generative AI, machine learning and ML. You can search for any tag. For example, I wondered how many biotech, and there were 4, as well as 1 biotechnology.

Share What You Observed

I know it’s a busy time of year, but if possible please share in the discussion below a few highlights from what you observed in going through the company list. In particular, I am interested in how you view the names chosen. Even if you just have time to post one observation, it will contribute to a really rich total discussion with so many eyes and minds from our community involved.

What Did I Notice?

Please hold off reading this section until you have browsed the names, and ideally noted what you found, but here are some things that attracted my attention:

• I was not surprised at how prevalent artificial intelligence was. Some are challenging to categorize, but I would say that AI is central to almost 2/3 of the startups in this list.
• I was impressed with the names. I described to someone that many of the names felt lively and almost magical. Not many boring names here. More of the names than I expected felt friendly.
• Names did not box in future direction changes, in most cases. That is particularly important for early stage companies.
• There were great one line descriptions. I felt that I could get a good idea what each was about in one, often rather short, phrase. A few examples, Retell AI is “Helping AI speak like humans.” Or Tusk, a pretty interesting name, also has a descriptive line “AI engineer and pushes and tests code.” Paradigm was one of my favourite names, and also has a great short description: “Every team needs an intern.”
• A number specifically mentioned Microsoft Copilot in their description.
• Two-word names are not that common, but a two-word name seemed more likely when the field was health. Some examples: Wattson Health, Simbie Health, Certainly Health, Flair Health, Health Harbor, Decoda Health, Empirical Health and others. As obvious from my list, it is more likely that health is the second term.
• A fair number of the companies do use AI in their name, usually as the second term. For example, Inventive AI, Quack AI, Letter AI, Artisan AI, Bronco AI, Watto AI, Spine AI, Neum AI, Reworkd AI, and others.
• While some companies referenced GPT in their description, usually not directly in their name. An exception is GovernGPT.
• Overall, creative spellings were not that popular, although there were some, such as Studdy, an AI math tutor, Salvy, Trayd, Roame and a few more.
• The majority of logos do not incorporate the name itself, and most were pretty simplified, stylized geometric icons. I guess I have become accustomed to the name-based logos used in brandable marketplaces, where the focus is the name, of course.
• Some names that used extensions other than .ai or .com built their name with extension right into their name and logo, smart to help counteract drain to a .com or .ai. For example, Line.Build, a service to help find tools and rebates to lower carbon footprint for buildings. As a side note, BuyDomains have the matching .com for sale, not that expensive. Other examples of logos incorporating the full name are Ten.Dev and Topo.io.
• The majority of names are 8 characters or less, although many longer as well. This references the official company name. Some use a longer domain name. One of the longer names was Andromeda Surgical, that provides autonomous robots for surgery. There were some really short names like Raz (they operate on the domain name TryRaz.com though) and SID, that does operate on sid.ai.
• A number append Labs as their second term, such as Surface Labs, Dioxus Labs, Kobalt Labs, and a few others.
• Not quite all, but most would pass the audio test. Only a few names would be difficult to spell and share.

If you are wondering about how Y Combinator works, this summary is pretty comprehensive. As well as benefiting from the experience, there is an investment of $500,000 in each company, in return for a share of that company.

It had been too long since I last went through a Y Combinator list of recent company names. I found this a useful exercise. I hope you did too.