Distinctive names are easier for AI models to retrieve. For an early-stage company, that can decide whether it shows up at all. Here’s what to check before you commit to a name.
Ask ChatGPT, Claude, Gemini and Perplexity for the best tool in your category, and watch what comes back. Some companies surface consistently across models. Others barely exist, sometimes with better products and more funding.
There are plenty of reasons for that, most of them to do with how much has been written about a company and where. One of them gets settled long before launch, usually in a naming workshop.
What we ask a name to do
Naming projects come with the same briefs and the same anxiety. The name has to do work: communicate the category, the benefit and the vibe, ideally all three, and immediately, the moment a stranger sees it.
But does the name really have to do all that work? The evidence has been building for decades. Google is a misspelling of a maths term. Amazon is a river, chosen partly because it started with A and would sort high in alphabetical listings. Häagen-Dazs is invented gibberish, engineered to sound vaguely Danish.
They were empty containers, and the companies spent years filling them with meaning until the name and the meaning became inseparable. So the advice for most of the last two decades was sensible: pick something you can live with, something pronounceable, ideally a bit clever so a stranger stops to think.
What happens when the customer asks a model
LLMs now field a growing share of your customers’ questions. Best CRM for a small agency. Best expense platform for a Series A company. Best way to run payroll across three countries.
The model answers from what it absorbed in training and, more and more often, from a web search it runs before replying. Either way, it has to work out which thing your name refers to.
That’s easy when a name appears almost nowhere else. Zapier and Monzo mean nothing apart from the companies, so every mention a model has seen of those strings points at the same place.
It gets harder with names like Bloom, Arc, Loop and Bolt. The model has seen these words billions of times, attached to gardening, geometry, crochet and plenty of other startups that made the same choice. Ask about Bolt and you might get a ride-hailing company, a checkout startup and an AI coding tool in one answer.
If you launched an expense platform called Loop tomorrow, the witty common-word name would be one weak association buried in a mountain of stronger ones.
Some of the qualities that made a name good for word of mouth and Google now make it harder for a machine to retrieve. Spellability mattered mostly because people typed names into browsers. For a model, the requirement is knowing, without ambiguity, that your string of characters points at you.
The obvious objection
Slack is a word for laziness, bolted onto software that exists to make workplaces more productive, and the contradiction has never cost it a customer. Notion, Linear and Stripe are ordinary words too. All four come up constantly when you ask a model about work software or payments.
They get away with it because of volume. Years of press, documentation, reviews and millions of people writing about them have given each word a dominant meaning in its category, and the models have learned it.
A company at Seed or Series A has a fraction of that signal. With a few hundred mentions on the web, there’s very little around the name to help a model tell you apart from everything else it could mean. A distinctive name makes sure those few hundred mentions count towards you.
The container argument still holds. The container changed.
A name will always matter to whoever reads it, though it can’t communicate everything about you. Its job was to be memorable, something the market could rally behind while the company filled it with meaning. The requirements were modest: human memory, a search bar, a spellable word.
Machine discovery adds a requirement at the very start, before you’ve shipped anything: the container has to be one a model can find.
A coined name only solves part of this. A model knows nothing about a brand-new word, so it won’t recommend you on the strength of the name alone. What a distinctive name gives you is a clean slot, where every mention you earn attaches to you, and filling it takes the same years of work it always did.
Our own name is a common word
Pony means a small horse, a small glass, a ponytail and, in British slang, twenty-five pounds. We’re aware of the irony of writing this under that name.
We kept it because six years of client work sit behind it, and changing it now would cost more than it saves. What we do instead is reduce the ambiguity around it. We use the exact same name everywhere it appears, one domain, and the same plain description of what we do beside it, so every mention reinforces the link between Pony and branding for tech companies.
It takes more deliberate effort than a coined name would, and that effort is worth knowing about before you choose.
Before the trademark and domain search
Ask five models who they name in your category. The companies that surface are your real shortlist competition, and their names show you what’s working.
Ask the same models what your candidate names mean. If one comes back as a yoga pose, something unfortunate in another language or three other startups, drop it. You want a name the model associates with nothing yet.
Weight coined and distinctive strings over dictionary words, especially if you’re early and won’t have much written about you for a while.
Search funded startups as well as trademarks. Check Crunchbase, Product Hunt, GitHub and the app stores. A name can clear legal review and still share a model’s attention with three companies that raised last year.
Once chosen, use the name identically everywhere. Site copy, directories, press, social profiles, llms.txt. Models learn the association from consistency, and every variant spelling splits the signal.
Describe what you do in the same plain words wherever the name appears, so models learn the connection quickly.
Everything after that works the way it always has. The company does the work and the name fills with meaning, until in a few years nobody remembers it could have been called anything else.
The checks above take about an afternoon. We now run them at the start of every naming project at Pony.
Pony Studio is the Emerging-Tech Brand Studio — a London-based branding and creative design agency specialising in strategic brand development for tech companies worldwide. If you’re building something bold and want a brand that moves at the same speed as your ambition, let’s talk.