Opportunities › Personal data removal from public brokers › Proposed app
Delist Desk
Step-by-step opt-outs and re-listing checks for your data broker profiles
- Score
- 21
- confidence 47
- Evidence
- 4
- items on the page
- Rivals
- 1
- named in sources
- First version
- 25 d
- estimate
- Type
- Mobile app
- PWA: installs on iPhone and Android
- Market since
- 2010
- Mature market · AI estimate
ScreensConcept
Mobile app: Users tackle data broker opt-outs on the go, step-by-step, following instructions and submitting removal requests as they have time between other activities. Sample screens on a phone, in the proposed brand. Their numbers are sample data.
Your exposure
7 open
- Phone number4 sites
- Home address5 sites
- Vehicle details2 sites
- Removed6 sites
- Awaiting reply3 sites
About this appAI proposal
Delist Desk helps you get your phone number, home addresses and vehicle details off data broker websites. It gives you the exact opt-out steps for each site, with pre-filled request text you can send yourself.
It is built for people who paid for a removal subscription and still found themselves listed. Every request has a status and a proof note, so you can see what was actually removed instead of trusting a promise.
Guidance is free. You pay once for automation and re-listing checks, not a monthly fee for something you can't verify.
- Tagline
- Take your details off the list, and check that it stuck.
- Voice
- PlainDirectCalm
- Why this name
- To delist is to remove a listing; a desk is where you sit down and get the paperwork done.
In the first version
Members say which features they would use. It tells PWAS what people want; it changes no score.
Broker-by-broker opt-out steps
Plain, numbered instructions for each broker, with direct links and the exact fields to fill in.
No member yet
Pre-filled removal requests
Generates request emails and form text from your details, ready to copy or send.
No member yet
Exposure checklist
Tracks where your phone, address and vehicle info appear, and what is still open.
No member yet
Proof of removal
Save a dated note or screenshot for each request, so you know what worked and what did not.
No member yet
Brand identityAI proposal
Check the name against trademark registers before using it.
Palette
#0F4C4ADeep Teal · primary#F7F4ECPaper · surface#1D2625Ink · text#D9822BAmber · accent#5E8C61Moss · data: removed
Typography
Aa
Delist Desk
ABCDEFGHIJKLMNOPQRSTUVWXYZ 0123456789
Take your details off the list, and check that it stuck.
PricingAI proposal
The material gives no competitor prices. These tiers follow the one-time-fee idea in the opportunity and are a starting point to test.
Guide
Free
- Step-by-step opt-out guides
- Exposure checklist
- Request text templates
Full clean-up
$39 once
- Pre-filled requests for every broker
- Follow-up drafts
- Proof trail
- Export of all records
Watch
$19 a year
- Re-listing re-checks
- Alerts when you reappear
- Refile in one tap
Would you pay Watch · $19 a year?
Your answer tells PWAS which prices people accept. It changes no score.
No answers yet.
What it could be worthEstimate
What a software business making this much sells for today, from real deals. Pick a monthly revenue.
If it makes
Worth about
$194,000
Sale range $132,000 to $263,000
$120,000 a year in revenue
From 87 software businesses listed and sold on Empire Flippers in the last year, revenue vetted by the broker: they sell for about 19× their monthly revenue, most between 13× and 26×.
Measured on profit, the middle deal is 32× monthly net profit: about 2.7 years of profit.
An estimate, not an offer or financial advice. A real price depends on profit, growth, churn, how much of the work is the owner's, and the buyer.
How it would growAI proposal
How the product would reach new customers through its own use, and how the first ones would be found. A plan to test, not a result.
- Built-in loop
- No loop in the product. Reaches customers through search, privacy communities and content. Users do not invite others or publish output to non-users in the core flow.
- Do they become customers?
- Test whether free-guide users convert to the paid clean-up or Watch tier, and whether people frustrated with failed subscriptions respond to a proof-based offer.
- First customers
- Privacy-conscious individuals in one country who already paid for a removal service and still see their phone and address listed.
- Where to reach them
- Hacker News and privacy forums: Share a free guide for a few brokers and ask for feedback.
- Search content: Write how-to pages on removing phone, address and vehicle listings from specific brokers.
- First milestone
- Fifty guide users and ten paying for the one-time clean-up within 60 days.
Why people already pay for this
- VerifiedHacker News post received 30 points and 9 comments
- Public claimPeople's personal information is publicly exposed on data brokers' websites and can be found easily
- AI inferenceExisting paid removal services fail to effectively remove data
- Public claimThere is demand for data removal solutions, demonstrated by willingness to pay for subscription services
Tech stack
Every proposal builds on the same PWA base, installable from the browser on any phone or computer. Dashed boxes are what this app adds.
- AppNext.js and TypeScript
- PWAManifest and service worker
- UITailwind CSS
- Data and authSupabase Postgres
- PaymentsStripe
- EmailResend
- HostingVercel
- This app · Scheduled jobsCron-based background job runnerRuns periodic re-listing checks and follow-up reminders.
- This app · Encrypted storageField-level encryption for personal detailsNames, addresses and plates are sensitive and must be protected at rest.
RisksAI inference
- DataBroker opt-out procedures change often; the guides need constant upkeep or they go stale.
- CommercialUsers may complete the free guide and never pay; one-time pricing limits recurring revenue.
- TechnicalAutomated form submission may be blocked by captchas or bot defenses at brokers.
- RegulatorySending requests on a user's behalf and storing personal data brings privacy law duties.
- CommercialProof that a listing is gone may be hard to verify automatically, weakening the core promise.
Everything marked AI proposal or AI inference was written by a model from the evidence on the opportunity page. The proposed name must be checked against trademark registers before it is used.