# Skyflow Financial Model

API-first Privacy Data Vault - a zero-trust cloud infrastructure layer that isolates, encrypts, and governs sensitive customer data (PII, payments, health) so enterprises can secure and use it simultaneously.

- Canonical: https://finamodel.com/startups/skyflow
- Excel download: https://finamodel.com/startup-models/skyflow.xlsx
- Category: Fintech
- Model type: SaaS ARR / Valuation
- Funding round: Series A
- Funding: $17.5M
- Founded: 2020
- Geography: US-headquartered; platform supports multi-region data residency (US, EU, APAC) [DECK slide 14]
- Customer: B2B

## About the company

Skyflow is an API-first Privacy Data Vault that isolates, encrypts, and governs sensitive customer data such as PII, payments, and health information. It lets enterprises use regulated data while reducing their exposure to storing it directly in operational systems.

The product is zero-trust infrastructure, sold through compliance, security, and developer entry points. Its Stripe and Twilio-like positioning suggests an enterprise SaaS relationship with a meaningful consumption component as customers store more records and make more API calls.

The model should forecast enterprise accounts, contracted ARR, implementation timing, vault records, API usage, and expansion. Separate platform licences from usage revenue, then model cloud, security, and support costs against each; long sales cycles and renewal rates are especially important sensitivities.

## 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

- Privacy Data Vault delivered as REST & SQL APIs
- Three vault archetypes: Payment Vault, Customer Vault, Patient Vault
- Core capabilities: polymorphic encryption, tokenization, access-control policy engine, data residency (US/EU/APAC), audit & provenance, cloud functions, multi-party data sharing, federated ML support
- Positioning: "Stripe for PII" - same simplicity/API abstraction that Stripe brought to card processing, Twilio to telephony
- Zero-trust architecture; designed for GDPR, CCPA, and data-residency compliance
- Sits between the customer's app backend and cloud services (AWS, Okta, etc.)

## Market

Competitive framing only: Skyflow positions itself as "Privacy Cloud" alongside Salesforce (CRM Cloud), Okta (Identity Cloud), MongoDB (Database Cloud), Snowflake (Analytics Cloud) - implying an enterprise-cloud-category ambition, not a point-solution.

## Revenue model

Implied from product architecture:
- API / consumption-based SaaS - comparable to Stripe/Twilio analogies cited on slide 12; likely priced per API call, per vault record, or per active customer record
- Enterprise subscription tiers possible for large-volume customers with compliance SLAs
- GTM entry points listed as: compliance failure, recent breach, cloud migration, new app build, microservices rewrite - suggesting land-and-expand via developer adoption leading to enterprise contract

## Traction & metrics

- Founded: 2019
- Engineering headcount: 35+ engineers
- Prior funding: $7.5M from Foundation Capital
- Marquee logos shown as company background / talent origin: PayPal, Oracle, Lyft, Salesforce, MuleSoft, athenahealth - these appear to be founder/team pedigree logos, not confirmed paying customers
- No revenue, ARR, customer count, growth rate, or NRR disclosed

## Competition / moat

- Moat framing: zero-trust vault was previously only buildable by Big Tech (implied by slide 10–11 referencing "leading tech companies had their own data vaults for years") - Skyflow democratizes this
- Competitive landscape not shown with named security/encryption competitors (no HashiCorp Vault, Protegrity, BigID, etc. called out)
- Differentiation claimed: polymorphic encryption, ability to run analytics & ML on fully encrypted data, developer-first APIs, multi-cloud data residency
- Positioning analogy vs. Stripe (payments) and Twilio (telephony) implies a platform/infrastructure moat once embedded in customer stacks

## Team & funding ask / use of funds

- CEO: Anshu Sharma - VP Product Salesforce (Force.com, AppExchange, Identity); PM at Oracle; Venture at Storm Ventures; co-founded Suki AI and Clearedin; board member; MS UNC, B.Tech IIT
- CTO: Prakash Khot - EVP & CTO AthenaHealth; SVP Engineering Salesforce; built data & analytics platform; founder & CTO DimDim; Director CA Inc.; 3x founder with exits
- Extended team: VP Cloud Infrastructure (Salesforce), VP Data Cloud (Oracle), CTO & Co-founder Suki Healthcare AI, Self-Driving Cars at Lyft, Architect AthenaHealth, CMO Heroku, PM MuleSoft, Encryption Lead Engineer, Architects at Salesforce and Microsoft
- Seed raised: $7.5M from Foundation Capital
- Series A: amount not disclosed; stated purpose "fund 10x growth"
- Use of funds: not broken out in the deck

## Recommended financial model

- **Archetype + why:** B2B SaaS ARR model with usage/consumption overlay. Skyflow is infrastructure SaaS with developer land-and-expand motion - ARR is the natural top-line metric; a consumption component (API calls, vault records) should layer underneath to capture the usage-based upside the Stripe/Twilio analogy implies.

- **Forecast horizon & granularity:** 5 years (Year 1–2 monthly, Year 3–5 annual). Series A raise implies 18–24 month runway to Series B milestones; monthly granularity in early years captures cash management for an infrastructure startup pre-profitability.

- **Key drivers & assumptions:**

| Driver | Value |
| -- | -- |
| Founding year | 2019 |
| Prior funding | $7.5M seed |
| Engineering headcount at deck date | 35+ |
| New logo adds per quarter (Yr 1) | 3–6 enterprise accounts |
| Average initial ACV | $80K–$150K |
| Net Revenue Retention | 115–130% |
| Gross margin | 70–80% |
| Sales cycle length | 3–6 months |
| CAC (blended) | $40K–$80K |
| LTV/CAC payback | 24–36 months |
| Headcount growth (engineering) | +8–12 engineers/quarter post-Series A |
| Opex as % revenue (Yr 1) | 400–600% (pre-scale) |
| COGS components | Cloud hosting (AWS multi-region), encryption compute, support |

- **Scenarios (Base / Bull / Bear - which variables flex):**
  - Bear: slow enterprise sales cycles, 2 new logos/quarter, ACV $80K, NRR 110% - runway stress-test
  - Base: 4 logos/quarter, ACV $120K, NRR 120%, gross margin 75%
  - Bull: developer-led PLG virality, 8 logos/quarter, ACV $150K, NRR 135%, faster gross margin expansion

- **Required sheets / outputs:**
  1. Assumptions - all drivers, scenario toggle (Base/Bull/Bear)
  2. ARR Bridge - new ARR, expansion ARR, churn, net new ARR by quarter
  3. P&L - Revenue, COGS, Gross Profit, S&M, R&D, G&A, EBITDA
  4. Headcount Plan - Engineering, Sales, CS, G&A; drives opex
  5. Cash Flow & Runway - operating burn, Series A proceeds, months to zero
  6. Unit Economics - CAC, LTV, payback period, LTV/CAC ratio
  7. Dashboard - ARR, customer count, NRR, burn multiple, runway

## Frequently asked questions

### Is the Skyflow financial model free?

Yes. The Skyflow 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.