Bootstrapped, confirmed through Stripe β and frozen six months ago
Open the real page βsupergrow.ai Β· alive as of 2026-08-31
A tool that writes LinkedIn posts in your own voice. Its MRR of $79,479 across 2,315 subscriptions was read through a Stripe connection, and it was built without funding. π΄ That connection has since expired, freezing the figures at 28 February 2026 β this is not a current number.
In plain words
It writes your LinkedIn posts the way you write them. Two people built it with no funding, and about $79,000 a month was confirmed through the payment system. β οΈ That confirmation stopped six months ago, so we do not know where it stands today.
The whole thing at a glance
To whom
People building an audienceβ¦
What
Micro-SaaS
Found how
The founder's own LinkedIn pβ¦
Paid how
Monthly SaaS
Flow: To whom, then What, then Found how, then Paid how
- Founder
- Deven Bhooshan
- Country
- IN
- Team
- β
- Startup cost
- β
- To first revenue
- β
- Automation
- high
- Reported revenue
- $79,479MRR Β· 2026-02
What is sold
Monthly SaaS, split between individual and team plans
Checked on the official site 2026-08-31 β individual Starter $19/mo Β· Pro $39/mo, Teams $139/month (4 accounts). Annual billing takes 20% off ($16 Β· $31 Β· $133). Seven-day free trial. β The cross-check holds β MRR $79,479 Γ· 2,315 active subscriptions = about $34.3 per subscription, sitting squarely between Starter ($19) and Pro ($39). Revenue and price list support each other.
Who buys
People building an audience on LinkedIn, and marketing or comms teams working together
What arrives is not what you keep
- What the customer paidThe number on the invoice
- AI toolsA share of the monthly subscription
- Platform feeDiffers by platform
- TaxDiffers by country and business form
- What is leftAt or below zero, it is not a price
This case does not publish its own tool costs, fees or tax. So we show the order and the items only β put your own numbers into the calculator.
AI's part and the person's part
Already had
A practitioner in LinkedIn personal branding. Not someone entering a new field because AI arrived β someone turning the repetition in his own daily work into a tool. To copy it, start from work you already do, not from learning AI.
If this is large, the AI is not the reason
What the AI did
Imitating your voice is the product. It drafts, rewrites, builds hooks and closing lines, and runs a 10β15 minute "AI interview" to pull a week of material out of you. A general chatbot also produces posts; what is sold here is getting them consistently in your voice.
the part a tool replaced
What the person did
Two people split product and marketing. The official page says Deven leads product and strategy while Utsav drives marketing and growth. β οΈ This is not a one-person product. And the founder had been doing LinkedIn personal branding for years β he knew where to sell it before he built it.
stories that omit this do not replicate
How customers were found
The founder's own LinkedIn presence β selling the tool where it is used
Product Hunt launch exposure
Conversion after the free trial
Paying customers
Checked on the official site 2026-08-31β¦
Flow: The founder's own LinkedIn presence β selling the tool where it is used, then Product Hunt launch exposure, then Conversion after the free trial, then Paying customers
How we verified this
Verified by a third party, e.g. payment-processor data
π΄ First, the thing that matters most β this is not a current figure. The TrustMRR page states "Stripe API key expired. Data last updated Feb 28, 2026". The number still came out of a payment system, but it is a snapshot frozen on 28 February 2026 because the connection lapsed. That is why we record the period as 2026-02. Confirmed (as of 2026-02-28) β MRR $79,479 Β· active subscriptions 2,315 Β· all-time $474,580. β Cross-check β the implied $34.3 per subscription falls between the published Starter ($19) and Pro ($39) prices. Two sources supporting each other. β οΈ Figures disagree inside the same page. MRR reads $79,479 while "last 30 days" reads $32,216. For a subscription business those should be close. It looks like the 30-day window decayed toward zero after the feed died, but we could not confirm that. So we publish only the clearly labelled MRR and leave the 30-day number out. Founder identity β the official `/about-us` page names Deven Bhooshan (CEO, co-founder) and Utsav Patel (CMO, co-founder) with their roles. π΄ Grade A says the revenue was real at that moment, and nothing more. Not that it still is, and not that one person could do it.
- TrustMRR β Stripe-verified, but β οΈ frozen at 2026-02-28 after the API key expired. MRR $79,479 Β· 2,315 subscriptions Β· $474,580 all-time (revenue_dashboard Β· checked 2026-08-31)
- Official site β co-founders named with roles (Deven Bhooshan CEO Β· Utsav Patel CMO) (official_site Β· checked 2026-08-31)
What made it work
It does not sell "writes posts" β it sells "writes them the way you do". A general chatbot produces posts too. The paid position is getting them consistently in your voice β a narrow slot right beside what general AI already does well. And it was sold where it is used. A LinkedIn tool marketed through LinkedIn activity: when the product and the traffic sit in the same place, distribution costs almost nothing.
Risks
- π΄ The number is six months stale. We cannot tell whether it grew or shrank since. Do not read it as current.
- Not a solo case β two co-founders, and the founder already had years in the field.
- It rides on one platform. A LinkedIn policy or API change moves the ground under the product.
- General models keep getting better at this. What stays defensible is voice fidelity and how deeply it sits in a real workflow.
Does this work in Korea?
This transfers to Korea comparatively well. LinkedIn use is growing among Korean professionals, and the product needs one capability, so start-up cost is low. What transfers is the order: turn the repetition in work you already do into a tool. He had been doing personal branding for years, so he already knew what was worth automating. β οΈ The place you sell it differs. Brunch, Naver or Instagram may be where your audience actually gathers. Decide whose repetition on which platform you are reducing before you pick the tooling.
Solo-feasible: no Β· Automation: high
7-day action plan
Step 1. Count whether you actually write something on a weekly cycle
if not, this model is not yours
Step 2. Split that writing into the part you do identically every time and the part that changes
Step 3. Hand only the identical part to an AI and check whether it still sounds like you
30-day action plan
Step 1. Record for four weeks what you must feed in to keep your voice intact
Step 2. Show that record to five people doing the same work and ask if they need it
Step 3. If they do, do it for them by hand and charge before you build any tool
Run the numbers
We do not print a single projected figure here. Put your own numbers in instead.
How this reads for you
Answer 13 questions and we work out what this case would take in your situation. Answers stay in this browser.
Find models that fit youGet the next verification result
We check the AI income stories people are talking about, grade the evidence, and send you what we found β including what we could not confirm.
Words you may not know
- Verification grade
- How far we checked this case. A means the revenue was confirmed by someone other than the founder; B means the business exists but the revenue is only the founder's word.
- Revenue
- Everything that came in. Tools, fees and tax still have to come out before it is what you keep. The two are not the same.
- MRR
- Money that arrives every month, as opposed to a one-time payment.
- Self-reported
- A number the person stated about themselves. Nobody else confirmed it, which is why we do not print those numbers.
- Replicability
- How likely someone else is to get a similar result. The more the founder already knew the field, the harder it is to copy.