<aside> 💡 Hybrid B2B2C model. Direct: ¥1,500/mo senior subscription. Family: ¥5,000/mo "Peace of Mind" dashboard for adult children. Municipal: ¥5M/year city-wide contracts for regional revitalization.

</aside>

Revenue Model (Hybrid B2B2G/D2C, Speculative Refinement)

Freemium core (free student "Explorers" as labor), DTC for seniors ("Mentors"), B2G for municipalities. Add speculative upsides: 10% Osekkai Point fees (redeemable rewards), 20% affiliate from health partners (e.g., Sompo AI integrations). Growth: 80% YoY DTC users post-pilot (SaaS norms), 1-2 new cities/month B2G (leveraging 1700 munis' tech interest). Launch Q1 2027; 2028 as Year 2 growth.

  1. Senior Subscription (DTC Tier): ¥1,500/mo (~$10). Value: Unlimited AI-bridged "Tea Times," isolation dashboards, family alerts. Conversion: 25% of free users (Duolingo-like).
  2. Municipal Contracts (B2G Tier): ¥5M/year/city (~$33K). Value: Subsidized access for 500-1K low-income seniors/city, aggregated "Social Vital Signs" reports for policy, Awaji-style revitalization.
  3. Student Tier: Free (gamified quests for language XP, vocab decks). Upsell: ¥500/mo premium (ad-free, advanced missions)—speculative 10% conversion.
  4. Additional Streams: Osekkai ecosystem (10% transaction fees on rewards), ads/partners (targeted health, non-intrusive).

2028 Financial Projection (Year 2: Post-Pilot Expansion)

Speculating expansion from Beppu/Awaji (Q1-Q2 2027 pilots: 1K users, 2-5 cities) to Fukuoka/Kobe majors, then national (e.g., Tokyo wards). User traction: DTC from viral AYF networks; B2G via METI subsidies. Scenarios grounded in 9-13% elderly care CAGR and $2.57B digital health funding trends.

  1. User Base & Traction (2028 Targets)
  2. ARR Calculation (Annual Recurring Revenue)
Scenario DTC Seniors DTC Revenue (JPY) B2G Cities B2G Revenue (JPY) Additional Revenue (JPY) Total ARR (JPY) Total ARR (USD)
Base 5,000 90,000,000 15 75,000,000 16,500,000 181,500,000 ~1,210,000
Optimistic 20,000 360,000,000 30 150,000,000 66,000,000 576,000,000 ~3,840,000
Pessimistic 3,000 54,000,000 10 50,000,000 9,900,000 113,900,000 ~759,000
  1. Cost Structure (Burn Rate)
Scenario Cloud/AI Costs (JPY) Dev Team (JPY) Sales/Marketing (JPY) Ops/Admin (JPY) Total Costs (JPY) Total Costs (USD)
Base 33,000,000 44,000,000 22,000,000 11,000,000 110,000,000 ~733,000
Optimistic 60,000,000 80,000,000 40,000,000 20,000,000 200,000,000 ~1,333,000
Pessimistic 24,000,000 32,000,000 16,000,000 8,000,000 80,000,000 ~533,000
  1. The Bottom Line (Profitability)
Scenario Total Revenue (JPY) Total Expenses (JPY) Gross Profit (JPY) Gross Profit (USD) Profit Margin
Base 181,500,000 110,000,000 71,500,000 ~477,000 39%
Optimistic 576,000,000 200,000,000 376,000,000 ~2,507,000 65%
Pessimistic 113,900,000 80,000,000 33,900,000 ~226,000 30%

<aside> 💡 Why PQ Wins: PQ targets measurable staff-capacity gains first, then tests whether earlier brain-health signals can reduce avoidable care escalation and insurance burden.

</aside>

Staff productivity capacity

Assumption: PQ reduces manual observation, engagement logging, and routine cognitive check-in burden by 5–15 minutes per resident per day.

Scenario Time saved / resident / day Staff hours freed / year FTE capacity created Value at ¥4M / FTE
Conservative 5 min 3,042 hrs 1.6 FTE ¥6.3M / year
Base 10 min 6,083 hrs 3.2 FTE ¥12.7M / year
Upside 15 min 9,125 hrs 4.8 FTE ¥19.0M / year