# Cipher Skin Financial Model Wearable sensor mesh platform that collects dense multi-modal data from human bodies and industrial objects to predict structural and functional failure before it occurs. - Canonical: https://finamodel.com/startups/cipher-skin - Excel download: https://finamodel.com/startup-models/cipher-skin.xlsx - Category: Hardware/Deep-tech - Model type: SaaS ARR / Valuation - Funding round: Series A - Funding: $5M - Founded: 2021 - Geography: US (founded Denver/Colorado area, implied); no international markets mentioned. - Customer: B2B ## About the company Cipher Skin builds wearable sensor mesh that captures dense data from people and industrial objects. The platform is intended to detect structural or functional deterioration before failure occurs, creating applications that combine physical sensing hardware with software interpretation of continuous data streams. The commercial model can blend sensor deployments with recurring software access and data usage. Enterprise adoption will depend on proving that dense sensing improves maintenance, safety, or performance decisions enough to justify installation and integration into existing operational workflows, often through long validation and procurement cycles. Model sensor deployments, units per customer, hardware ASP, software subscriptions, data usage, and expansion by use case. Deduct sensor manufacturing, installation, connectivity, cloud processing, analytics, field support, and enterprise sales costs. Pilot conversion, deployment scale, hardware margin, data usage, sales-cycle length, and renewal should drive scenarios. ## What's included - 5-year monthly revenue build with stage-appropriate growth assumptions - Full P&L, headcount plan, and operating-expense schedule - Cash-flow statement, runway, and burn-rate tracking - Valuation via exit multiple with a DCF cross-check - Returns analysis with MOIC and IRR - Unit economics including CAC, LTV, payback, and cohort retention ## Product & value proposition 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. ## Market - 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). ## Revenue model 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. ## Traction & metrics - Seed raised: $1.35M - Employees: 20 - Patents: 9 granted US patents, 18+ pending - Products shipped: Pipe Sleeve, Knee BioSleeve, Arm BioSleeve, BioHelmet ## Competition / moat - 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. ## Team & funding ask / use of funds **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. --- ## Recommended financial model **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 ## Frequently asked questions ### Is the Cipher Skin financial model free? Yes. The Cipher Skin model is a free Excel download with live formulas. ### Can I change the assumptions? Yes. The workbook is editable and its live formulas recalculate when assumptions change.