SEO and marketing decision
Radarkit
A technical user can build a limited tracker and basic agents, but reproducing RadarKit's scraping scale, residential-IP prompting, and production-ready agents/reporting is operationally heavy and better kept as a paid service.
Visit website↗$29/mo
$348/yr
Read off the official pricing page.
$100one-off70 h to build
$200/mo6 h/mo upkeep
On cash alone, building overtakes the subscription at 8 seats.
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
- Prompt AI chat UIs, collect responses, extract citations, rank and report visibility, generate agent-driven outreach/content actions.
What it still won’t have
- Residential IP prompting/scraping scale and anti-blocking infrastructure
- Polished UI, reporting, and branded PDF client reports
- Built-in, production-ready agents with action credits and managed follow-ups
- Enterprise features (SSO, dedicated manager, SLA, API access) and documented guarantees
What remains hard
- Infrastructure at scale
We don't use APIs, we visit the ChatGPT, Gemini, Perplexity, etc. websites directly and then prompt your keywords.
- Infrastructure at scale
Get location-specific results we use residential IPs to prompt your keywords.
First-year cost
Keep paying
Paying is—cheaper in year one.
On cash alone, building overtakes the subscription at 8 seats.
Money you would actually spend
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
Build a minimal AI-visibility tracker using Node.js, Puppeteer, Postgres, Express, and React. In scope: (1) a Puppeteer-based scraper that opens ChatGPT and Perplexity web UIs, submits a list of tracked prompts (configurable), captures full responses and metadata, and stores raw results in Postgres; (2) a server-side parser that extracts cited domains/links and simple sentiment from responses and computes per-keyword visibility and average position; (3) a basic agent service that drafts outreach emails using templates and sends via Gmail API and another that outputs WordPress-ready content suggestions; (4) a React dashboard showing tracked keywords, recent citations, top cited domains, and simple export (CSV); (5) background scheduler to run prompt refreshes. Out of scope: large-scale residential-IP rotation/anti-blocking, multi-model coverage beyond two test models, branded PDF reports, SSO, enterprise SLA. Include error handling for scraping failures, rate limits, retries, input validation, and unit/integration tests for the scraper, parser, and API endpoints.
How we checked
How the score was reached
- Partly verdict base52
- 3 cited sources+3
- Price verified on pricing page+3
- 3/3 assessment runs agreed+4
- Hard moats found in the evidence-3
- Evidence score59
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 →Cited sources · 3
Every page the run actually retrieved.
- official productRadarKit product
- official pricingRadarKit pricing
- official docsRadarKit Agents feature
Integrity checks
What held up, and what did not.
