# DivvyCloud Financial Model Enterprise cloud security and governance platform that autonomously enforces compliance and security policies across multi-cloud infrastructure. - Canonical: https://finamodel.com/startups/divvycloud - Excel download: https://finamodel.com/startup-models/divvycloud.xlsx - Category: Enterprise/Security - Model type: SaaS ARR / Valuation - Funding round: Series B - Funding: $19M - Founded: 2019 - Geography: HQ Arlington, VA (Washington D.C. area); customers are U.S. enterprises [DECK, slide 13]. - Customer: B2B ## About the company DivvyCloud provides cloud security and governance software that autonomously enforces policies across multi-cloud infrastructure. The platform is aimed at enterprises that need a consistent way to identify and remediate security, compliance, and configuration risk across cloud accounts. It is sold as subscription software through direct and channel routes, placing it in the cloud security posture management market. The commercial case is based on reducing manual cloud-governance work while giving security teams greater control as infrastructure and policies scale. The model builds enterprise ARR from new customers, average contract value, channel contribution, expansion, and renewals. Deployment and cloud-delivery costs sit below revenue, while sales capacity, partner economics, gross margin, and operating expense assumptions determine cash requirements. ## 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 - Platform harvests cloud infrastructure data via native cloud APIs, unifies it into a standardized data model, analyzes for policy deviations in real time, and autonomously remediates (notify → record → correct). - Core workflow: Harvest → Unify → Analyze → Act. Policy logic built via "BotFactory" (user-defined bots). - Deployment: containerized, deployable behind customer firewall or in customer cloud account(s) - not a pure SaaS hosted product. - Use-case pillars: Governance (unified visibility, tag policy, control plane), Security (network, IAM, data protection, DLP), Compliance (PCI-DSS, HIPAA, CIS, NIST 800-53). - Key differentiators: autonomous remediation (not just alerting), extensible platform-first architecture, flexible deployment model. ## Revenue model - Annual Contract Value (ACV)-based subscription model - explicitly stated as metric. - Direct enterprise sales (primary) + channel sales (referenced as a growth lever). - Pricing basis not disclosed in deck - likely per-resource, per-account, or seat-based; enterprise SaaS at this stage commonly anchors to cloud resource count or number of cloud accounts managed. - Average ACV implied: $173k total ACV across 34 customers = ~$5.1k average ACV per customer; likely skewed by a few large accounts given 12/34 are Fortune 500. ## Traction & metrics - 34 customers total. - 12 of 34 customers are Fortune 500. - $173k total ACV across all customers. - ARR figure intentionally redacted in deck ("XXX ARR XX") - confirmed by image review, slide 3. - Only 1 enterprise customer lost in 6 years of operation - implies very low gross churn. - 50 employees, majority based in Washington D.C.. - $10M raised over company lifetime (pre-raise). - Logo customers include Twilio, Discovery Communications, Nike, GE, Kroger, Fannie Mae, Ancestry, Autodesk, Fidelity Investments, Turner, Adobe, 3M. ## Unit economics Implied/derived only: - Implied average ACV per customer: ~$5.1k. - Churn rate: extremely low (1 lost customer over 6 years across ~34 customers) - implies net revenue retention likely >100% for enterprise cohorts. ## Competition / moat - Problem framing positions existing monitoring/reporting tools as insufficient ("security monitor, not security guard" - alerting without action). - Moat claims: autonomous remediation vs. alert-only competitors; extensible platform architecture; flexible deployment (on-prem or cloud) vs. pure-cloud alternatives; 6-year head start on enterprise relationships. - Named competitors: not identified in deck. ## Team & funding ask / use of funds **Team (slide 4):** - Brian Johnson - CEO / Co-Founder - Chris DeRamus - CTO / Co-Founder - Peter Scott - COO / CFO - Chris Hertz - CRO - Jeremy Snyder - VP of Sales - Scott Totman - VP of Engineering **Funding ask (slide 12):** - Raising $20M. - Use of funds: Enterprise Sales (grow direct + channel), Innovation (contextual intelligence / additional data), Marketing (ABM, events, brand), Product (productization of known use cases). - No ownership/valuation/cap table disclosed. --- ## Recommended financial model **Archetype + why:** SaaS ARR / ACV-based enterprise model. Revenue is annual subscription driven by ACV per customer; the metric language, enterprise sales motion, and use-of-funds allocation toward sales headcount are all classic enterprise SaaS patterns. **Forecast horizon & granularity:** - 3–5 year annual model with monthly detail for Year 1 (to support the $20M raise use-of-funds narrative). - Monthly in Year 1, quarterly in Years 2–3, annual in Years 4–5. **Key drivers & assumptions:** *Revenue drivers:* - Starting customer count: 34 - New logo adds per year: 10–15 in Year 1, scaling to 20–30 by Year 3; rationale: $20M raise is partially funding sales headcount growth from a currently small team - Average ACV per new logo: ~$75k–$150k for new enterprise wins; $173k total ACV ÷ 34 customers yields a ~$5k blended average, but this appears suppressed - Fortune 500 logos (Nike, GE, Adobe, Fidelity) at enterprise scale would suggest much higher ACVs for key accounts; blended may be dragged down by smaller/earlier customers - ACV expansion rate per existing customer: 10–20% NRR expansion on multi-cloud growth; rationale: cloud sprawl grows organically and more clouds = more accounts/resources to govern - Gross churn rate: <5% annually; rationale: only 1 customer lost in 6 years across ~34 implies <0.5% annual churn historically - Net Revenue Retention: 105–115%; rationale: very low gross churn + likely upsell on resource growth *Cost drivers:* - Headcount: 50 employees currently; use-of-funds implies significant sales + engineering hiring with $20M - Gross margin: 70–80%; rationale: containerized deployment behind customer firewall reduces hosting cost; professional services / onboarding may compress margin slightly - S&M as % of revenue: 40–60% in near term (sales-led, enterprise motion, ABM + events); compress to 25–35% at scale - R&D as % of revenue: 20–30% - G&A: 10–15% *Capital:* - Pre-raise cash raised: $10M over company lifetime - Current raise: $20M **Scenarios (Base / Bull / Bear - which variables flex):** - Bear: New logo adds 8/year, ACV flat, no NRR expansion, higher churn (3%) - Base: New logo adds 12/year, ACV grows modestly, NRR ~110%, churn <2% - Bull: New logo adds 20/year, ACV step-up from Fortune 500 expansion, NRR 120%+, channel sales contribution kicks in by Year 2 **Required sheets / outputs:** 1. Assumptions dashboard (all drivers in one place, color-coded by source) 2. Revenue build: customer count waterfall (new logos, expansions, churn) → ARR bridge → ACV schedule 3. P&L: Revenue, COGS, Gross Profit, S&M, R&D, G&A, EBITDA, Net Income 4. Headcount plan: by department, linked to opex 5. Cash flow & runway: monthly for 24 months post-raise, shows when the $20M is consumed 6. Unit economics summary: CAC, LTV, LTV/CAC, payback period (inputs will need values) 7. Scenario toggle: single toggle cell switching Bear / Base / Bull ## Frequently asked questions ### Is the DivvyCloud financial model free? Yes. The DivvyCloud 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.