How to name an AI company
The naming space is flooded, 'AI' terms can't be trademarked, and the obvious moves are already taken. Here's why it's hard - and what the smart names actually did.
Let's say you're starting an AI company. You open a naming brainstorm doc and write down your first ideas. They probably look something like this: NeuralFlow. CogniCore. DeepSync. IntelliBase.
Now go search any of those on Google. You'll find a startup using each one. Some have raised money. One of them probably has a trademark dispute in progress.
The AI naming space isn't just competitive - it's saturated in a way that's different from other industries. Everyone is building in the same conceptual territory, using the same vocabulary, with the same instinct to signal intelligence and automation. The result is a sea of names that blur together.
Naming an AI company is harder than naming almost anything else right now. Here's why - and what to do about it.
The numbers are stark
In Y Combinator's Winter 2024 batch, 23% of companies chose .ai domains - and 28 companies (about 11% of the batch) put some version of "AI" directly in their name. By the Summer 2025 batch, 88% of the companies were AI-native. That's not a niche anymore. That's the whole cohort.
88%
YC S25 companies classified as AI-native
Extruct AI Research, 2025
23%
YC W24 companies using .ai domains
Smart Branding analysis, 2024
2M+
Registered trademarks in US Class 9 today (vs ~23K four decades ago)
River + Wolf / Lexicon
When nearly every startup in the most influential accelerator is an AI company, the naming pressure compounds fast. Every obvious word in the semantic neighborhood of "intelligence" has already been claimed - in some form, in some jurisdiction, by someone.
The word "AI" is a trap
The first instinct most founders have is to include "AI" somewhere in the name. It signals category membership. It helps with early SEO. It tells investors and customers immediately what you're building.
Three reasons this backfires.
"AI" as a term is legally unprotectable. The USPTO rejected OpenAI's application to trademark "GPT" outright, ruling it a generic descriptor for a class of language models. "ChatGPT" got a similar rejection - "merely descriptive" of the product's function. If you can't trademark the most famous AI product name in history, building defensible IP around anything that leans on AI-adjacent terminology is a long shot.
The ".ai" domain extension is already crowded in a way that erases differentiation. When a quarter of your competitor class all share the same extension, the extension stops meaning anything. Naming agency River + Wolf noted that the ".AI suffix" trend "represents the opposite of innovation" and predicted it would feel meaningless by 2027.
The one founders underestimate: "AI" might date your company. Tech naming history is littered with prefixes and suffixes that felt essential and now feel like relics - "e-" (e-commerce, e-learning), "digital," "cyber," "mobile." "Cloud" survived. Most didn't. Whether "AI" joins the survivors is a genuine open question, and betting your brand on it is a real gamble.
The homogenization trap runs deeper than the AI suffix
Even if you skip the AI suffix, there's a broader vocabulary problem. Certain words have been so thoroughly colonized by AI companies that using them now just signals "we are an AI company" without actually distinguishing you from any other AI company.
A partial list of terms that are effectively exhausted: Neural, Cognitive, Deep, Alpha, Synth, Cortex, Nexus, Vision, Core, Logic, Pulse, Flux, Node. These words aren't inherently bad. They were good once. Some led to genuinely memorable brands. But at this point, the pattern is too recognizable - CogniCreate Labs, SynthoMind Solutions, VirtuVerse AI. These read like outputs from a naming AI that hasn't seen enough interesting data.
The "Copilot" metaphor is another example. It started as a clever aviation reference - the AI as your co-pilot, not the pilot. By now, it's been used so many times across so many products that it's ceased to function as a brand differentiator at all. Microsoft's saturation of the term didn't help.
Warning
If your brainstormed name sounds like it was generated by an AI naming tool, it was probably generated by hundreds of other founders using the same tool. Check your shortlist against Product Hunt, Crunchbase, and the USPTO TESS database before getting attached.
What the best AI names actually did
Look at the AI companies with genuine brand recall - not just name recognition because of product ubiquity, but actual brand resonance. Almost none of them followed the obvious playbook.
Anthropic
AI safety / LLMs
Named after the anthropic principle in cosmology - the idea that the universe must be compatible with the observers in it. Nothing in the name says AI. Nothing needs to.
Mistral
AI models
A powerful cold wind that sweeps through southern France - the name comes from Occitan. It's a French company making a point about European identity, and the name carries that without explaining it.
Midjourney
AI image generation
"We are all midjourney: we have a rich past behind us and an unimaginable future ahead." The company said that. Nothing in the name points at AI. That's the whole move.
Perplexity
AI search
In NLP, perplexity is a mathematical score for evaluating how well a language model predicts text. It also happens to describe the feeling you have before you find an answer. The product is literally the cure for perplexity.
Cohere
Enterprise AI
No AI, no suffix, no category signal. Just a word that suggests alignment and coherence. The restraint is the point - it sounds like a company that doesn't need to explain itself.
Hugging Face
ML developer tools
Warm, weird, and human in an industry that runs cold. It's uncomfortable to say in certain boardrooms. That discomfort is what makes it impossible to forget.
Grok
AI assistant (xAI)
From Heinlein's "Stranger in a Strange Land" - to grok something means to understand it so thoroughly you become part of it. A sci-fi word that signals a very specific kind of depth. Either you know the reference or you learn it.
Claude
AI assistant (Anthropic)
Named after Claude Shannon, who founded information theory. Deliberately a male name - Anthropic wanted to break from the pattern of female-coded AI assistants (Alexa, Siri, Cortana, Gemini).
Look at what they share: none of them tried to describe what the product does. Not one leaned on "AI" for identity. They're human names, weather patterns, physics principles, science fiction verbs, a philosophical stance about being mid-process. The name carries feeling, not function.
The strategic question nobody asks first
Before deciding whether to put "AI" in your name, there's a prior question: what is this name supposed to do over the next ten years?
If you're building a narrow vertical tool - AI for dental billing, say, or AI for contract review - including "AI" can work fine. The category signal is useful, the audience is specific, and brand longevity is less of a concern than immediate clarity.
If you're building something that might grow well beyond its initial AI-powered feature, the name needs room to breathe. Google, Apple, Amazon - none of those names describe what the company does. That's not an accident. It's what gives a brand permission to expand into anything.
| Naming approach | Examples | Trademark strength | Longevity risk | Best for |
|---|---|---|---|---|
| Invented word | Anthropic, Cohere, Grok | Strong | Low | Ambitious long-term brands |
| Nature / place metaphor | Mistral, Rainbird, Moonvalley | Strong | Low | European / differentiated brands |
| Human name | Claude, Jasper, Alexa | Moderate | Low | Humanized AI products |
| Philosophical / abstract | Midjourney, Perplexity | Strong | Low | Creative / search / discovery tools |
| Word + AI suffix | Stability AI, Shield AI | Weak (AI = generic) | High | Short-term clarity, vertical tools |
| Descriptive compound | NeuralFlow, CogniCore | Very weak | High | Avoid |
Strategy comparison based on trademark strength, longevity, and brand potential
The timing problem: naming before you're ready
Siegel Gale, a naming consultancy, pointed to Google's handling of Bard as a cautionary tale. Google named and launched their AI assistant publicly while it was still demonstrably behind competitors. The brand "Bard" accrued negative associations - limitations, playing catch-up - that became impossible to shake. Hence Gemini.
Bard wasn't a terrible name. The problem was naming a half-finished product publicly and letting the brand absorb all the "behind competitors" associations before the product could carry its own weight. One approach that's worked for some companies: launch beta versions under a generic descriptor like "[CompanyName] AI," then introduce a distinct brand name once the product is ready to carry it. You get market feedback without burning a brand name on an unfinished product.
Practical moves before you name anything
Before you get attached to a name, run it through USPTO's TESS database for trademark conflicts. Class 9 (electronics, software) now holds over 2 million registered marks - up from roughly 23,000 four decades ago. The odds that your shortlist is clean are not great. Also check Crunchbase and Product Hunt, then do a plain Google sweep for negative associations. You'd be surprised what comes up.
Domain availability matters, but .com isn't the only option. Plenty of credible companies operate on .ai or .io without issue. What matters more is owning the exact brand match somewhere and not sitting confusingly close to a competitor.
Tip
If a name passes the domain check but fails the trademark check, it's still off the table. A great name you can't protect is a liability, not an asset - you'll spend money building brand equity around something someone else can legally use.
The real reason it's hard
AI startup naming is hard because the entire industry is trying to name itself using the same vocabulary at the same moment in history. Everyone is working on intelligence and automation - and the English vocabulary for those concepts is limited. Not small, but well-picked-over.
The companies that broke through didn't find the one unclaimed word in the neural/cognitive/deep bucket. They looked somewhere else - a wind system in France, a Heinlein novel, a 1948 math paper, the deliberate oddity of two humans embracing.
When the obvious territory is taken, you either pick something forgettable from what's left, or you change the map entirely.
Based on trademark strength, naming agency analysis, and category saturation data
If you're working through the naming process for an AI company and want a co-creator that knows the terrain - what's overused, what's legally risky, what actually travels across languages and markets - NameFirst was built for this.
References and sources
- Smart Branding: Y Combinator W24 Batch Domain Analysis - domain extension and naming pattern data
- Extruct AI: YC S25 Batch Analysis - 88% AI-native company statistic
- River + Wolf: What to Call It - Trends in AI Naming - homogenization analysis, naming pattern critique
- Siegel Gale: How to Pick a Name for Your AI Startup - Google Bard timing lesson, strategic naming framework
- Gerben IP: GPT Too Generic for Trademark Protection - USPTO trademark rejection details
- Fast Company: Why AI Companies Are Bad at Naming Their Models - model naming confusion analysis
- Bitnewsbot: ai16z Rebrands to ElizaOS - trademark pressure rebrand example
- Focus Lab: Brand Naming in 2026 - current naming trends
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