SEO and marketing decision

Namerobo

A competent technical user can reproduce the core functionality (LLM-based name generation + RDAP availability checks) in about a week and modest monthly upkeep, so build is realistic and cost-effective compared with continuing to pay for a hosted product.

Visit website
You pay

Not priced

No pricing page we fetched carried a figure, so there is nothing to compare against. The build side is still real.

You’d pay instead

$50one-off24 h to build

$30/mo3 h/mo upkeep

No published price to break even against.

No open-source build does this yet

Nothing published replaces this one, so a replacement starts from an empty file. Here is what it would have to cover.

What a replacement has to do

  • User submits a plain-English prompt → call an LLM to generate candidate names → filter candidates for content rules and duplicates → check availability via RDAP for selected TLDs → display available names and link to registrars.

What it still won’t have

  • Affiliate linking and established registrar partner relationships (referral UX and potential affiliate tracking)
  • Any bespoke ranking or proprietary prompt-engineering tweaks used by the live site
  • Polish of an existing product (UX copy, blog, edge-case handling for many TLDs)

What remains hard

  • Product polish and ongoing maintenance
Read the build prompt

First-year cost

No published price

Namerobo does not publish a price we could read, so there is nothing to compare against. What building costs is below.

Money you would actually spend

Keep paying
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Subscription price × seats × 12

Build it
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AI build —APIs + hosting —

Time you would spend

—

—

What you would spend

What we assumed

The verdict above measures whether you could build it. This one is only about money.

Runnable build prompt

Not run yet
Build a minimal AI domain-name discovery web app using Next.js (React) + Node backend, PostgreSQL (optional) and OpenAI-compatible LLM API. Core features in scope: (1) single-page Web UI for a plain-English prompt and TLD selection, (2) server-side prompt parser that extracts keywords/tone, (3) LLM request/response pipeline to generate 20 candidate names, (4) RDAP client that performs live availability checks for each candidate+TLD and flags unsupported TLDs, (5) results page that shows only available names and provides registrar links, (6) basic logging, error handling, and unit/integration tests for the parser, RDAP client, and LLM integration. Out of scope: advanced price-compare scraping across registrars, bulk-upload workflows, user accounts, and affiliate payout plumbing. Require retries and timeouts for RDAP/LLM calls, input validation, rate-limit handling, simple CI, and tests covering main flows.
How we checked2 sources · 2/3 runs agreed · evidence score 79

How the score was reached

  • Build verdict base78
  • 2 cited sources+1
  • Evidence score79

The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time - so the same evidence always produces the same number.

How scoring works →

Integrity checks

What held up, and what did not.

! 2 of 3 runs agreed; the verdict is the majority✓ Citations limited to fetched pages! 1 moat recorded