We help creators know why their video works — or how to fix it — before they publish. The craft stays theirs.
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Problem
Every creator runs the same six steps. Most of it is hope.
01
Set the goal
02
Find the idea
03
Write the script
04
Shoot until it's good enough
05
Edit
06
Post — and pray
repeat · every post · every day
Most AI tools replace the creator. Lomero sharpens the creator.
Team
I built Lomero because I needed it. Then strangers found it.
Eight steps. An hour per Reel-post. I ran the manual chain — download MP4, transcribe, paste into Claude, frame,
refine, post — for months before I built a script to skip it. Within weeks, strangers were finding my tool
through ChatGPT. That's when I knew this wasn't my pain alone — it was a category.
Nick Krykunov
Solo founder · ex-CTO Neural Dynamics
9 yrs in tech
30+ platforms shipped
3 → 25 engineers
Co-founded and scaled Neural Dynamics from 3 to 25 engineers as CTO. Shipped 30+
platforms across SaaS, CRM, ERP, AI, fintech for US, EU, and Asia clients. Built Lomero
solo in 8 weeks — full product, open signup, organic AI-search distribution.
First two hires:Full-time CMO (distribution + content) ·
Full-stack engineer (RAG + pipeline).
Two recent AI workflows I've shipped to enterprise clients — selected to show range across real-time
pipeline ops and document automation:
Russmedia — Swiss media intelligence
AI ad-intelligence pipeline
Replaced manual newspaper ad review with end-to-end AI pipeline. Custom extraction
model, Perplexity enrichment, Looker analytics.
Three things are true simultaneously. They weren't 18 months ago.
01
Generation cost → zero
Veo 3, Sora 2, Runway, Luma. Text-to-video down ~80% in 18
months. Within 12 months, generating a short-form video will cost less than a text message.
Selection becomes the scarce resource.
02
Content is now C-suite
Netflix CCO runs $17B budget. PayPal hired Head of Content inside
CEO's office. 419 open Director/Chief Content Officer roles at $120-230K base —
fintech and non-media included.
Lomero is the quality layer for the AI content era. Sits between generation and publishing.
The dataset is the moat.
Validation
Next-gen companies are built on content, not funded into it.
The sequence flipped. Creators
build audience first, then build the business around it. Content stopped being a marketing function — it became
the acquisition engine.
MrBeast
→ Feastables
Audience first. Chocolate brand reportedly $250M+ run rate. Traditional CPG can't match the
CAC.
Emma Chamberlain
→ Chamberlain Coffee
YouTube audience converted to CPG. $7M Series A, nationwide distribution, cult following.
Alex Hormozi
→ Acquisition.com
Daily content as deal flow. Portfolio of 10+ companies he wouldn't have accessed without the
audience.
Alex Cooper
→ Unwell Network
Podcast audience into creator network. Monster Energy partnership. Nine-figure SiriusXM
deal.
The industry calls it the same way
Gary Vaynerchuk
"Document your work. Build in public. Content is the best business card of the decade."
Naval Ravikant
"Earn with your mind, not your time. Build an audience. The internet rewards leverage."
Alex Hormozi
"Content is the cheapest way to build leverage that compounds for a lifetime."
Dan Martell
"The best founders are the best storytellers. Content is how you scale trust."
Kevin O'Leary
"If you don't have a personal brand in 2026, you don't exist. Full stop."
Mark Cuban
"Attention is the scarcest resource. Content is how you earn it."
The Promise
What every user can hold us to.
Whatever you shoot, you'll know why it works — or how to make it work — before you publish.
How we deliver it · four beats
Tells
you why a video worked
Shows
how top creators handle the same problem in your niche
Walks
you to the specific fix
All
of it pre-publish — never after
Post knowing. Not hoping.
Product + Unit Economics
Three product layers. Three cost stages. Margin expands as we ship deeper.
L1 ships during the Stage 1→2 transition. Deeper product + lower cost compound together. By month 6
we're a 92% gross margin business with a closed-loop dataset competitors can't catch up to.
Moat
AI models commoditize. The data is the moat.
Data flywheel
1More videos analyzed
↓
2More outcome data captured
↓
3Better recommendations
↓
4More creator trust · more analyses
Source 1 · Fuel
Public-influencer trend data
Pattern library across niches, formats, creator tiers. Re-creatable by competitors with 6 months +
budget. Table stakes. Not the moat.
Source 2 · The engine
Closed-loop outcome data (L3)
Our brief → user shoots → real-world result. Per-user, per-niche. Compounds with every active user.
Nobody else has this. Can't be scraped retroactively. Platforms won't build it —
conflicts with their ad model.
Anyone can call GPT-5. Almost nobody is structured to capture the brief→outcome pair from day one. We
are.
Competitive landscape
Two categories. They build libraries that generate scripts. We sharpen the creator with a closed-loop
dataset.
Their category
Outlier database + AI script generator
"Find a viral video → remix it → write a script from it." Descriptive. No feedback.
Generation, not coaching.
Our category
Pre-publish sharpener with closed-loop outcome data
"Why your video works, how to make it work, before you publish." Prescriptive. Compounds
with every user.
Their category is generation. Our category is coaching.
Sandcastles built a fancy viral database. We built a creator-sharpener with a closed-loop dataset that compounds
with every user.
Wedge · ICP staircase
Beachhead first. Expand outward as each layer monetizes.
Why a 2026 product: Generation cost only crossed the "free" threshold in 2025 · AI
search (ChatGPT, Perplexity) now refers users to tools they don't know exist · Content leadership became a
C-suite function in the last 18 months.
Current
01 · Beachhead
Creators & Founders
Brand/marketing course creators are the wedge. High intent, teach distribution, convert
because Lomero reinforces their curriculum. 4-8 Reels/week, commercial intent.
M4-6
02 · Fast-follow
Clipping Studios
Highest paid willingness per effort. First real ARR proof. Multi-client workspace,
white-label PDF, batch scoring.
M7-12
03 · Expansion
Short-form Agencies
Revenue diversification. Multi-account workflows. Natural extension of clipping studios.
Year 2
04 · Venture prize
In-house Content Ops
419 open Head of Content roles today. Budget-new buyer. Teams > 10 editors. Upmarket
prize.
Each tier unlocks the next. Free tier serves the belief — everyone deserves a real shot at
building a brand. Paid tiers come from creators with commercial intent.
Traction · As of 2026-05-17
Open signup since April 20. ChatGPT is the #2 distribution channel. $0 spent on
marketing.
30
Registered users (Clerk)
~27 organic from marketing · 3-5 new signups /
day
110
↑ 20.9% WoW
Weekly active users (GA)
$0
Marketing spend to date
Traffic mix · last period · 567 sessions
Direct28.92%
ChatGPT (combined)28.22%
Google referral14.11%
Google organic9.35%
Search Google referral4.94%
Twitter (t.co)2.82%
AI search refers users who didn't know we existed — the moat starting.
Engagement quality
58.9%
Engagement rate
1m 50s
Avg engagement
7.1%
GSC avg CTR (3mo)
6.5
GSC avg position
It actually shows me what to do next with my videos. I'd love to show this to my students. Let's talk
partnership.
— Unsolicited inbound · employee at an SMM agency running courses for content
marketers
The Ask
$350K
Pre-seed · 12 months runway
Full-time Engineer + CMO from M2
Three metric-gated phases · Foundation → GTM → Scale
Seed-ready M12 at $3-8M post-money
See Capital Plan → for the per-category breakdown
Capital plan + return
$350k · 12 months · Every dollar accounted for
Category
Q1
Q2
Q3
Q4
Year
Founder ($5k/mo)
15.0
15.0
15.0
15.0
60.0
Engineer FT (M2 start)
10.0
15.0
15.0
15.0
55.0
CMO FT (M2 start)
12.0
18.0
18.0
18.0
66.0
Outsource (brand · SEO · UX · data ops)
10.0
4.5
4.5
4.5
23.5
Personnel subtotal
47.0
52.5
52.5
52.5
204.5
Marketing ads
3.0
7.0
10.0
10.0
30.0
Compute + AI APIs
2.0
3.0
4.0
6.0
15.0
Office (Lisbon-band · M3 start)
1.6
4.8
4.8
3.3
14.5
Travel + Partnership
1.0
2.0
4.0
3.0
10.0
Subscriptions (eng + mkt + biz)
1.5
2.0
2.5
2.5
8.5
Equipment (one-time)
8.0
—
—
—
8.0
Legal (incorp + contracts)
3.0
1.0
0.5
0.5
5.0
Accounting
0.5
0.7
0.7
0.6
2.5
Hiring (screening tools)
2.0
—
—
—
2.0
Insurance D&O (M6 start)
—
0.25
0.75
0.5
1.5
Non-personnel subtotal
22.6
20.75
27.25
26.4
97.0
Buffer / contingency (14%)
10.4
12.75
12.25
13.1
48.5
Quarterly total ($k)
80.0
86.0
92.0
92.0
350.0
All figures in $k USD ·
Cumulative draw: 23% → 47% → 74% → 100% · Avg monthly burn $29.2k · EU base, geo locked at first investor
commit
