CS

Cipher Skin Financial Model

Three-layer stack:

1. Cipher Mesh - flexible sensor mesh that wraps cylinders and flat surfaces; measures movement, strain, temperature, moisture, vibration, biometrics simultaneously across the full object.
2. Digital Mirror™ - iOS/iPad app that renders real-time 3D visualization of the monitored object from the mesh data stream; displays biometrics dashboard (heart rate, blood pressure, O2 saturation, HRV, VO2, EKG, respiration rate/depth, lactic threshold).
3. Cipher Cloud - cloud data aggregation via API; builds longitudinal dataset enabling predictive analytics and failure prediction.

Go-to-market model: customer-sponsored co-development → 90-day pilot (product package purchase) → multi-year data subscription conversion.

Current products (shipped): Pipe Sleeve, Knee BioSleeve, Arm BioSleeve, BioHelmet. Upcoming products: BioLegs (leggings), BioShirt (tee-shirt). Product roadmap tied to "cylinders monitored": Sleeve (1 cylinder, 12 mo) → Leggings (2 cylinders, 24 mo) → Tee-Shirt (3 cylinders, 36 mo).

IP: 9 granted US patents, 18+ patents pending.

• Combined TAM across sample applications: >$700 billion by ~2023–2026.
• Life sciences (majority): $650 billion by 2024.
• Remote monitoring: $27 billion by 2023.
• Oil & gas monitoring: $9 billion by 2026.
• Market sizing methodology: Third-party market figures cited without sources; used to frame opportunity, not bottoms-up. Figures aggregate very different markets (life sciences is broadly defined).

Two-part model implied by the co-development process slide:

1. Hardware / product package sale - upfront purchase of Cipher Skin product package (device + Digital Mirror app + initial cloud access). No price points disclosed.
2. Multi-year data subscription - recurring contract for Cipher Cloud data aggregation, access to anonymized database, and predictive analytics insights. No pricing tiers, ASP, or contract lengths disclosed.

Channels: Direct enterprise sales (pilots with early partner customers); trade shows mentioned for marketing. Consumer vs. enterprise: Primary go-to-market is enterprise/institutional (athletic teams, industrial operators, healthcare providers), not direct-to-consumer.

• Seed raised: $1.35M
• Employees: 20
• Patents: 9 granted US patents, 18+ pending
• Products shipped: Pipe Sleeve, Knee BioSleeve, Arm BioSleeve, BioHelmet

• Moat claims (from product/vision slides): 9 granted patents + 18+ pending; proprietary "Cipher Mesh" sensor architecture capturing simultaneous multi-modal data pinned to a common timeline across the full object (vs. isolated point sensors); unique longitudinal dataset accumulating in Cipher Cloud.

Founders:

• Phillip Bogdanovich (CEO) - former USMC Recon Corpsman, former Tactical Medical Chief (Dept. of State), Harvard Business School; two prior tech startups taken to several million dollars in revenue.
• Dr. Shaka Bahadu (Co-founder) - Weill Cornell MD, Stanford GSB MBA; healthcare ops / clinical informaticist; experience at two Y Combinator digital health startups pre- and post-Series A.

Key hires: CSO (Ph.D. biosignals), Head of Engineering (PhD computer science, wearable tech), VP Marketing, mechanical engineers (sports + biomedical), electrical engineer (ex-Lockheed Martin).

Round: Series A (size not stated).

Use of funds (categories, no dollar amounts):

• Engineering & Legal: software dev (full stack, back-end, mobile iOS, data science, QA), pilot manufacturing, materials/equipment, university research, sponsorships, patent filing, FCC licensing.
• Sales & Marketing: sales reps, customer success, product marketing, trade shows.
• Operations: COGS for operating/supporting pilots, office operations.

Note: Deck references a "Detailed Proforma" as a separate document - actual Series A ask size and proforma financials are not in this deck.

Archetype + why: Hardware + SaaS subscription (two-part IoT revenue model). The business sells a physical sensor product upfront (one-time hardware revenue) then converts customers to recurring multi-year data subscriptions (recurring SaaS-style revenue). The appropriate model is a hardware + recurring revenue 3-statement model with separate hardware P&L and subscription ARR build, similar to a med-device / industrial IoT company. Not a pure SaaS model because hardware COGS and inventory are material. Not a marketplace. Not M&A/SPAC.

Forecast horizon & granularity:

• 5-year annual model (Year 1–5), monthly in Year 1 to reflect pilot conversion dynamics.
• Year 1 = sleeve commercialization ramp; Year 2 = leggings added; Year 3 = tee-shirt added. Align to roadmap milestones.

Key drivers & assumptions:

*Revenue - Hardware*

• Units sold per product line per year: start 50–200 units/year in Y1 (pilot-stage enterprise, not consumer scale); scale 2–3x annually as commercialization completes.
• ASP hardware per unit: $1,500–$5,000 depending on product (BioSleeve vs. Pipe Sleeve); enterprise hardware pricing typical for medical-grade wearables. No deck data.
• Product lines active: Sleeve Y1, Leggings Y2, Tee-Shirt Y3.

*Revenue - Subscription*

• Pilot-to-subscription conversion rate: 60–70%; 90-day pilot window.
• Annual subscription ASP per customer: $10,000–$50,000/year (enterprise contract for cloud data + analytics); no pricing in deck.
• Contract length: 2–3 years (deck says "multi-year"); model as 3-year.
• Churn rate: 10–15%/year annual logo churn; early-stage enterprise benchmark.
• Subscription lag: 90 days post hardware sale before subscription starts.

*COGS*

• Hardware COGS: 50–60% of hardware ASP at pilot volumes; expect improvement to 35–45% at scale; typical for custom IoT hardware.
• Subscription COGS (hosting, support): 15–20% of subscription revenue.

*Opex*

• Headcount: grow from 20 employees today to ~40 by end Y1, ~65 by Y2, ~90 by Y3 per roadmap investment.
• Engineering & Legal spend: ~50% of Opex in Y1 (software-heavy build-out).
• Sales & Marketing: ~25–30% of Opex; ramps with commercialization.
• Operations: ~15–20% of Opex.

*Balance sheet / cash*

• Series A raised: $5–$10M (not stated in deck; typical range for an IoT/wearable startup at this stage with $1.35M seed already raised).
• Runway target: 18–24 months post-raise.
• Inventory: will need working capital model for hardware builds; 60–90 days inventory on hand.

Scenarios (Base / Bull / Bear):

• Flex variables: pilot-to-subscription conversion rate, hardware ASP, subscription ASP, sales cycle length, headcount ramp, Series A size.
• Bear: Conversion rate 40%, low ASP, slower product launches (Leggings delayed to Y3).
• Base: Conversion rate 65%, mid ASP, roadmap on schedule.
• Bull: Conversion rate 80%, premium ASP, industrial (pipe) channel takes off alongside bio, faster hiring.

Required sheets / outputs:

1. Assumptions dashboard (all drivers in one place, toggle scenarios)
2. Revenue build - Hardware: units × ASP by product line
3. Revenue build - Subscription: cohort waterfall (new customers, conversions, churned, total active)
4. Income Statement (monthly Y1, annual Y1–Y5): hardware revenue, subscription revenue, hardware COGS, subscription COGS, gross profit, Opex by category, EBITDA, D&A, EBIT, interest, taxes, net income
5. Balance Sheet (annual): cash, inventory, PP&E, deferred revenue, equity
6. Cash Flow Statement (annual): OCF, capex, financing (Series A)
7. Headcount schedule by department
8. Unit economics summary: hardware gross margin %, subscription gross margin %, blended gross margin %, LTV/CAC (once CAC assumptions added), payback period
9. Runway / cash waterfall chart