Opportunities › AI search visibility optimization for brands › Proposed app
Citewise
See which AI answers cite your pages, learn why, and fix gaps in your own voice
- Score
- 41
- confidence 52
- Evidence
- 6
- items on the page
- Rivals
- 2
- named in sources
- First version
- 40 d
- estimate
- Type
- Desktop app
- PWA: runs in the browser, installs on Mac and Windows
- Market since
- 2023
- Emerging market · AI estimate
ScreensConcept
Desktop app: Marketing teams analyze detailed citation patterns, edit drafts with voice review, and interpret complex analytics reports from a desk. Sample screens on a computer, in the proposed brand. Their numbers are sample data.
Prompt tracker
Sample data38%
About this appAI proposal
Citewise shows marketing teams where their brand appears in AI search answers. You list the prompts that matter, and it re-checks them on a schedule across AI engines. It records which pages are cited, which competitors are cited instead, and when that changes.
For each prompt where you are missing, it explains the likely gap: the sub-questions an engine may split the prompt into, the facts your page leaves out, and structure that is hard to quote. It then drafts edits for a person to review, using your style notes and approved facts.
It treats AI visibility as a series of experiments. Every change is logged against citations and AI bot requests, so the team builds its own evidence about what works instead of following myths.
- Tagline
- Find out what AI cites, and why. Then earn it.
- Voice
- PlainEvidence-ledCalm
- Why this name
- Cite plus wise: knowing which sources AI engines cite, and acting on evidence rather than myths. Two plain syllables, easy to say.
In the first version
Members say which features they would use. It tells PWAS what people want; it changes no score.
Prompt tracking
Add the questions your buyers ask. Citewise re-runs them on a schedule and records which sources each AI answer cites.
No member yet
Fan-out view
See a prompt split into likely sub-queries, so you can find which sub-question your pages fail to answer.
No member yet
Page diagnosis
Each page gets a plain list of gaps: missing facts, vague claims, buried answers and weak structure.
No member yet
Voice-locked drafts
Drafts follow your voice notes, approved facts and banned phrases. Nothing goes live without a named reviewer.
No member yet
Brand identityAI proposal
Check the name against trademark registers before using it.
Palette
#0F4C4ADeep Teal · primary#F7F4ECPaper · surface#1B2422Ink · text#E8A317Marigold · accent#C4553BClay · alert, losses#7FA38FSage · data
Typography
Aa
Citewise
ABCDEFGHIJKLMNOPQRSTUVWXYZ 0123456789
PricingAI proposal
The material gives no competitor prices. These tiers are a starting point to test, scaled by prompts tracked and automation level, as the opportunity suggests.
Watch
$49 a month
- 25 tracked prompts
- Weekly checks
- Page diagnosis
- Weekly brief
Improve
$149 a month
- 100 tracked prompts
- Daily checks
- Voice-locked drafts
- Experiment log
- Log upload
Team
$399 a month
- 400 tracked prompts
- CMS draft push
- Reviewer roles
- Multiple brands
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
- Shared outputs. Teams share weekly visibility reports and read-only experiment pages with executives, clients and agencies, who see the Citewise name on them.
- Do they become customers?
- Report readers are often budget holders such as agency clients or managers. Test whether report links lead to trials, and whether agencies bring client brands onto paid plans.
- First customers
- Content and SEO leads at mid-size B2B software companies, 20 to 200 staff, who report falling Google referrals and publish a blog weekly.
- Where to reach them
- Hacker News and SEO forums: Share open experiment write-ups on what moved AI citations, and invite readers to run the free check.
- LinkedIn: Post before-and-after citation cases and offer free audits to content leads.
- Small SEO agencies: Offer agencies a multi-brand plan so they can add AI visibility reports to client work.
- First milestone
- Ten paying B2B software teams on the Improve tier within 90 days, with at least half running a logged experiment.
Why people already pay for this
- VerifiedHacker News post received 36 points and 27 comments
- AI inferenceMarketing teams are seeing declining traffic due to Google's AI Overviews and AI search engines answering queries directly.
- Public claimThe space around AI visibility is poorly understood: few rigorous studies, many myths (e.g., conflicting advice on llms.txt), and unclear best practices.
- Public claimAI search engines expand single queries into multiple fan-out queries and use ranking algorithms similar to RFF to determine which pages are sourced.
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 · AI answer collectionLicensed AI search APIs or a result-collection serviceNeeded to run tracked prompts on AI engines and read the cited sources reliably.
- This app · Background jobsScheduled job queueRecurring prompt checks and log processing run outside web requests.
RisksAI inference
- PlatformAI engines may restrict automated querying or change output formats, which could break prompt tracking or raise collection costs.
- DataAI answers vary between runs and users, so a single check may be noisy. Citation rates need repeated sampling and honest confidence labels.
- AIGenerated drafts may be inaccurate or generic. Human approval and an approved-facts list are required, which slows the automation promise.
- CommercialThe evidence is public claims from one forum thread. Teams may not yet pay for AI visibility, and larger SEO suites may add similar features.
- TechnicalShowing cause and effect is hard. Edits may coincide with other changes, so experiment results could be over-read.
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.