Sansan
👤 Chika Terada (Ex-Mitsui trader who chased a contact for months, then found a colleague already knew them — networks are invisible.)🌐 siteLinkedIn
Every business card your firm collects becomes one shared contact database — humans verify each scan, not just OCR.
Will it work? · our read
Earned data moat. A dull office ritual became a company-wide contact graph, verified by humans not just OCR — real switching cost. The catch: physical cards are fading.
01How the money moves
Staff collect
business cards
business cards
→
AI + human ops
digitize to 99.9%
digitize to 99.9%
→
Firm-wide contact
cloud → subscription
cloud → subscription
02The numbers
¥41.5B
ARR (May 2025)
IR filing
99.9%
scan accuracy
sansan
+27.5%
FY25 sales YoY
IR
Scan centers in Japan, Singapore & Thailand key every card by hand — Sansan deliberately refused to trust pure OCR. Sansan IR
ARR passed ¥41.5B (about $280M) as of May 2025, up 27.5% YoY — first-party from Sansan's IR (TSE: 4443). The business now spans Sansan, Bill One & the free Eight app.
03Weight class — CENTStap an axis
Control High
Owns the verified contact graph across client firms; cards keyed in-house, not scraped — deep switching cost.
04The key move
Humans in the loop
Everyone bet OCR would read business cards. Terada saw it fumble Japanese names, so Sansan pays humans to key each card by hand. That 'inefficient' choice bought 99.9% accuracy — the trust that is its moat.
fact
The counter-intuitive move
The bet only paid because Terada had lived corporate Japan's card ritual — he knew enterprises would pay for accuracy, not speed.
our read
05Where the moat is
Not the software (contact apps are cheap). It's:
Process · human scan centers at 99.9% accuracySwitching · firm-wide contact graph locks clientsScale · free Eight app feeds the data + brandBrand · Japan's default card-data cloud
06How it diesmedium confidence
Business cards keep fading as work goes remote and digital, shrinking the wedge. If the pivot to invoices (Bill One) stalls, Sansan is left guarding a contact graph that fewer people keep feeding. our read
Show evidence · counter
Evidence: Card exchange is fading post-remote-work (the weak Need axis); growth now leans on Bill One invoices, not cards.
Counter: But 18 years of firm-wide switching cost + the human-accuracy moat are hard to unwind — and Bill One is already the fastest-growing line.
07Against rivals
Free apps are OCR-only and mangle names; big CRMs make you type every contact. Sansan sells the one thing both miss — a card database that's actually correct. our read
08Who uses it
🏢 Enterprise sales teams — shared contact graph🤝 B2B firms in relationship-heavy Japan🧾 Finance teams — Bill One invoices👤 Individuals — free Eight app
★Would it work for you?
Is there a boring, high-frequency ritual in an industry you know where data is created constantly but never captured cleanly?
Terada's edge: lived corporate-Japan context + nerve to put humans where rivals trusted OCR. We don't score you — you answer.
🚀Use it as a launchpada prompt for your own AI
Copy → paste into your AI → then develop it freely in the conversation.
You are a sharp, honest startup strategist. Use the proven case below as a launchpad for MY idea — help me find my own angle, not copy it.
<my_profile>
Domain I know: [your domain]
My unfair advantage (access/audience): [your edge]
Interests: [your interests]
Resources & goal: [your resources] · [your goal]
</my_profile>
<case name="Sansan" model="data">
What it does: digitizes every business card a company collects via AI + human operators (99.9% accuracy) into a firm-wide contact-data cloud; Japan, TSE-listed, ¥41.5B ARR
Why it won (moat): not the app (card scanners are cheap) — the human-verified accuracy + firm-wide switching cost
Weakest axis (CENTS): Need axis: physical card exchange is fading post-remote-work
How it could die: cards fade + invoice pivot stalls → guarding a graph nobody feeds
</case>
<task>
Be a skeptical operator, not a cheerleader. No generic startup platitudes. If my angle is weak, say so plainly.
First, a reality check: markets like this mostly fail. State the honest base rate (how crowded/hard is this?) and the ONE specific thing that would have to be true for ME to be the exception — grounded in my profile above.
Then a compact table:
- Fit — does this pattern suit my edge, or fight my gap?
- Angle — my sharpest differentiation vs Sansan (concrete, not "better UX")
- Distribution — exactly where my first 100 users come from (this is the hardest part — be specific, not "content marketing")
- Risk — its "how it dies" (above) in MY situation
Finish with one line: "The single thing to do next."
Use only the facts above; if data is thin, say so — never invent numbers.
Then stay with me and go deeper on whatever I ask — tech stack, rough cost & time, the smallest MVP to test, pricing, or timing.
</task>
✓ Copied — paste into your AI
👤Placeholders like [your domain] auto-fill from your profile — example values for now.Set up profile →
Sourcesupdated · daily
· Founder & story — Disrupting Japan (Terada)· IPO & scale — The Edge Singapore· ★Revenue / ARR ¥41.5B — Sansan IR (Annual Report 2025)· 99.9% accuracy & product — sansan.com/en/features
Revenue is first-party: ARR ¥41.5B (about $280M) as of May 2025 from Sansan's IR filings (public co, TSE 4443) — FILED, not estimated. The 99.9% accuracy & human scan centers are Sansan's own claims. Founding story from Terada's interviews. CENTS & the 'dies' read are ours. We never score you.