# Athennian Financial Model Cloud-based legal entity management system (EMS) uniting entity data with workflow and document automation. - Canonical: https://finamodel.com/startups/athennian - Excel download: https://finamodel.com/startup-models/athennian.xlsx - Category: Enterprise/Security - Model type: SaaS ARR / Valuation - Funding round: Series A - Funding: $5.5M - Founded: 2021 - Geography: North America primary; workflows described as "consistent globally" implying international expansion ambition [DECK slide 5]. - Customer: B2B ## About the company Athennian is a cloud-based legal entity management system for law firms and corporate legal and compliance teams. It combines entity data, governance workflows, ownership records, document automation, reporting, tax support, and integrations in one system. The company replaces legacy software, binders, and spreadsheets used to manage complex legal entities. Its revenue is recurring subscription income, supported by multi-year contracts and expansion potential as customers bring more entities, users, and workflows onto the platform. The model uses an ARR cohort build anchored in ACV, contract duration, new customers, retention, and expansion. A secondary entities-or-seats driver explains upsell within each account, while sales efficiency, gross margin, operating costs, and cash runway show the economics of the enterprise legal-tech motion. ## 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 - First cloud-native global EMS launched in 2017; incumbent competitors (Computershare, CT Corporation, CSC, Diligent/Blueprint, Secretariat/Bridgeway) launched in the 1980s–1990s. - Replaces pre-internet software, binders, and spreadsheets for legal departments and law firms managing high volumes of legal entity data and workflows. - Feature pillars: Governance, Ownership, Compliance, Data Reporting, Tax, Integrations. - Value prop: Automating entity data accelerates transactions, defends tax planning, avoids audit/government friction, reduces reputational risk. - EMS positioned as a common data platform used by all three parties: Entity Software providers, Professional Services Firms, and Corporate Teams. ## Market - NA Software TAM: US$2.5B (2018), growing at CAGR of 13.18% (2014–2018). - NA CoSec Services TAM: US$835.5M (2017), growing at CAGR of 7.3% to US$1.44B by 2025. - Combined addressable spend: US$3.5B+ annually on legal entity management software and CoSec services. - Market dynamics described as similar to eDiscovery (a market that consolidated around cloud-native players). ## Revenue model - SaaS subscription; metrics presented include ACV (Annual Contract Value) and ARR (Annual Recurring Revenue), confirming annual subscription pricing. - Contract length tracked in years (Avg. Contract Length metric visible), suggesting multi-year enterprise contracts. - Customers appear to be law firms and corporate legal/compliance teams. - Channel (direct, reseller, partner): Not explicitly stated; sales motion implied by Velocity/days-to-close metric. ## Traction & metrics - Slide 4 is a "2020 Revenue Performance" dashboard with the following metrics listed: 2020 Exit ARR, 2019 Exit ARR, ACV, Avg. Contract Length (yrs), Lifetime Value, CAC, Velocity: days to close won, Lead > MQL, MQL > SQL, 2021 Entry Pipeline. - ALL numeric values in the table are rendered as "########" (column overflow artifact in the source file) - no actual values are legible from the image. - The "Active Entities vs. ARR" area chart (slide 4) shows strong upward trajectory for both series from Oct 2019 through Oct 2020, with a steep acceleration beginning approximately Jul 2020. Entities (red line) appear to slightly outpace ARR (blue area) in the final quarter, suggesting the customer base grew faster than revenue in late 2020. No axis labels with values are legible. ## Unit economics - Metrics tracked: LTV (Lifetime Value), CAC, and LTV/CAC ratio is derivable from those two. - Actual values: Not readable (all "########" in slide image). - Avg. Contract Length in years is tracked - implies LTV is calculated as ACV × Avg. Contract Length (or a churn-adjusted variant). ## Competition / moat - Named incumbents: Computershare, CT hCue (Wolters Kluwer), CSC, GEMS, Diligent/Blueprint, Bridgeway/Secretariat - all launched 1980s–1990s. - Moat claim: First EMS built this century; cloud-native vs. legacy on-premise/pre-internet tools. - Competitive dynamics compared to eDiscovery (where cloud disrupted incumbent players). - Specific differentiation on features (Governance, Ownership, Compliance, Data Reporting, Tax, Integrations). ## Team & funding ask / use of funds --- ## Recommended financial model - **Archetype + why:** SaaS ARR model. Revenue is clearly subscription-based with ACV/ARR/LTV/CAC metrics. Multi-year contracts with enterprise buyers (law firms, corporate legal) means a cohort-based ARR build with net revenue retention is the right structure. Secondary layer: seats or entities as a usage/expansion driver if pricing is per-entity. - **Forecast horizon & granularity:** 5-year annual (2021–2025) with monthly detail for Year 1. Series A context warrants a 5-year horizon to show path to profitability. - **Key drivers & assumptions:** | Driver | Value | | -- | -- | | 2020 Exit ARR | Unknown - not readable in deck | | 2019 Exit ARR | Unknown - not readable | | YoY ARR growth rate (Year 1) | ~100–150% | | YoY ARR growth rate (Years 2–5) | Decelerating: 80% → 60% → 40% → 30% | | ACV | Unknown | | Avg. Contract Length | Unknown (years) | | Gross margin | 70–75% | | CAC | Unknown | | LTV | Unknown | | LTV/CAC ratio | >3x - standard SaaS benchmark; likely higher given multi-year contracts | | Net Revenue Retention | 110–120% | | Churn rate (gross logo) | 5–8% annually | | S&M as % of revenue | 40–50% (early) declining to 25–30% | | R&D as % of revenue | 20–25% | | G&A as % of revenue | 10–15% | | Lead > MQL conversion | Unknown | | MQL > SQL conversion | Unknown | | Sales velocity (days to close) | Unknown | | 2021 Entry Pipeline | Unknown | - **Scenarios (Base / Bull / Bear - which variables flex):** - **Base:** ARR growth ~120% in Year 1, NRR 115%, gross margin 72%, S&M efficiency improving gradually. - **Bull:** ARR growth ~180% (chart trajectory holds), NRR 125%, expansion into global markets begins Year 3. - **Bear:** Growth decelerates to ~70% in Year 1 (macro friction, slow enterprise sales cycle), NRR 105%, higher CAC. - Primary flex variables: ARR growth rate, NRR, CAC, ACV, gross margin. - **Required sheets / outputs:** 1. Assumptions - all drivers, centralized, labeled or 2. ARR Waterfall - new ARR, expansion, churn/contraction, net new ARR by period 3. Cohort Model - customers by cohort, retention curve, LTV build 4. P&L - Revenue → Gross Profit → EBITDA → Net Income 5. Sales & Marketing - pipeline funnel (Leads → MQL → SQL → Won), headcount-driven CAC 6. Headcount Plan - by function (S&M, R&D, G&A) 7. Cash & Runway - burn rate, cash balance, months of runway post-Series A 8. Scenario Toggle - Base / Bull / Bear switcher feeding P&L and ARR Waterfall 9. Dashboard - ARR, NRR, CAC, LTV, LTV/CAC, gross margin, burn multiple ## Frequently asked questions ### Is the Athennian financial model free? Yes. The Athennian 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.