My Company Shares a Name With 185 Beetles. Reddit Would Say I'm Doomed.
Araptus is a genus of bark beetle. Family Curculionidae, subfamily Scolytinae. Between one and three millimetres long. Several species were first described from cacao pods in Ecuador and Brazil.
It is also the name of my software company.
I found this out properly the way anyone finds anything out properly — by auditing it, expecting a disaster, and discovering the disaster was somewhere I hadn't thought to look.
named Araptus
are beetles
actually ranks
first appears
Why Name Collisions Got Worse
In classic search a namesake was a nuisance. You'd rank alongside them, and anyone who genuinely cared could add a word to the query and separate you in a second.
In AI answers it's structural. Language models resolve entities by proximity in a vector space, and two things sharing a name with overlapping context are genuinely difficult to keep apart. The failure modes are worse than "we both show up":
- The bigger entity absorbs the smaller one, and your work is attributed to them
- Their reputation bleeds onto you — which matters enormously if they've done something bad
- Or the model decides you don't exist, and that you're a misspelling of the famous one
People have been merged with namesakes accused of crimes. For a business, being told by a confident assistant that you aren't real is a trust problem you can't argue your way out of.
So when I found 185 entities carrying my company's name in the structured database the knowledge graph leans on — and every single one was an insect — I assumed I had a serious problem.
What I Actually Found
Buried Under Taxonomy
- Beetles crowding the results page
- The brand buried under species records
- Assistants confidently describing an insect
- A rescue mission
We Win, Decisively
- The company at #1, with five sitelinks
- Then social profiles and business directories
- The beetle's first text result around #6
- Otherwise beetles appear only in the image strip
Google resolves the brand correctly, and it isn't close. The collision is real, but it's confined to the structured layer — the database, where the name still resolves unanimously to a genus of insect.
That matters, because the structured layer is disproportionately what AI entity resolution reads. But it's a very different problem from "we're losing the search results," and conflating the two would have had me spending months fixing the wrong thing.
I went looking for beetles.
The beetles were fine. What I found instead was that every third-party source describing my company had it wrong — and I had written most of them myself.
The Description, Not the Namesake
I read every profile that describes the company from the outside. Business directories. Review platforms. Social profiles. Every one of them described a web development and digital solutions company.
That is what a model reads back when someone asks what Araptus is. Not the beetle — the label.
And here's the uncomfortable part. Those descriptions weren't written by strangers who misunderstood. I wrote them, years ago, when that's what the business was. The company changed. The descriptions didn't. The entire external record of what this company does was frozen at a version of it that no longer exists.
Your entity isn't what you say you are on your own website. It's the consensus of what everyone else says you are — and most of that is text you wrote once and never looked at again.
Define, Distinguish, Corroborate, Close
Four moves, run in order. Each one feeds the next, and the last closes the circuit so the engines reinforce the distinction themselves.
Define
Publish consistently about what the entity actually is, on every surface that ranks. Social posts count here — not for traffic, but as corroborating signal. Half a million impressions in a year converted to roughly fifty site visits. Judge it as entity-building, not clicks.
Distinguish
On your own property, state the difference explicitly and back it with machine-readable markup — organisation and person nodes with stable identifiers and a complete set of identity links. Models observably quote this language back at you.
Corroborate
Get other people to say it. Interviews, podcasts, earned coverage. You saying it is necessary and weak on its own; independent confirmation is what the model actually weights.
Close the loop
File the structured record last, once the content, the markup and the third-party sources all agree — so every signal points at the same identity and reinforces the others.
What I shipped
The on-site half is done, and it was worse than I thought before it was fixed. The homepage typed itself as an Article, with the organisation demoted to a publisher sub-node carrying no identity links at all — those had been attached to the person instead.
It now emits a proper entity graph with stable identifiers on every page, where before it was on none. Company profiles moved onto the organisation. The unambiguous form of the name — the one nothing else on earth competes for — is registered as an alternate name. And the homepage carries a catalogue of seven named software products, so the machine-readable identity is a software company that makes things, rather than a services vendor.
What I'm Deliberately Not Doing Yet
The obvious final step is filing a structured-database record for the company. I have it drafted, verified, and deliberately not submitted.
The bar for those records is low but real, and entries on small companies do get deleted as non-notable or promotional. A deletion leaves a public log entry attached to the brand — which is meaningfully worse than having no record at all. The sequence matters: corroborate first, file second. Filing early is the one move in this whole process that's hard to undo.
Rewriting the third-party descriptions is higher leverage than anything else on the list, and it costs nothing. It's also the step everyone skips, because it isn't building anything.
How to Test Your Own — Ten Minutes
Entity resolution is contextual, so test it like an experiment rather than asking once and believing the answer:
- Your brand name alone, then with your city, then with your industry, then common misspellings
- Logged in versus logged out
- A cold session versus one already primed with related conversation
- Across several assistants — they resolve differently, and you fix each where it's wrong
- Watch whether your own pages get quoted back. That's the signal the work is landing.
Record every answer before you change anything. Without a baseline you can't tell whether you fixed it or the model just reshuffled on its own.
I expected to write a post about a funny name collision and a hard technical fix. What I actually learned was duller and far more useful: I had been maintaining an accurate description of my business in exactly one place, and it was the one place that counts least.
If you've repositioned in the last few years — new products, new focus, new market — the odds are very good that the internet still describes the old version of you, in words you typed yourself.
The bottom line
I went looking for a beetle problem and found a description problem.
Machines describe you using what other people wrote about you. Go and read it — you probably wrote it, and it's probably out of date.
Sources & Method
- Wikidata — the genus record and associated species entities
- GBIF — taxonomic records for the genus
- Araptus — how this site presents itself to machines
- Araptus — about the company
Method. Entity count taken from a direct database search for the brand name. Result positions captured from a live, logged-out search results page in August 2026. Structured-data changes verified across the full page set of this site. Entity resolution drifts constantly — anyone reproducing this should re-run it rather than rely on these positions.
