# Apollo Financial Model Apollo builds and sells an enterprise "data graph" platform (powered by GraphQL) that sits as a unified API layer between frontend apps and backend microservices. - Canonical: https://finamodel.com/startups/apollo - Excel download: https://finamodel.com/startup-models/apollo.xlsx - Category: Dev Tools - Model type: SaaS ARR / Valuation - Funding round: Series D - Funding: $130M - Founded: 2021 - Geography: US-HQ, global enterprise customer base implied - Customer: B2B ## About the company Apollo provides an enterprise data-graph platform built around GraphQL, creating a governed API layer between front-end applications and distributed backend services. It helps teams query data safely while allowing services to evolve without breaking product experiences. Revenue combines enterprise product subscriptions, freemium developer adoption, and support contracts. Its go-to-market blends developer-led product usage with top-down enterprise sales, making the free graph a source of signals and pipeline for larger accounts. The model is an enterprise SaaS ARR waterfall with a PLG feeder. New enterprise logos, contract value, freemium conversion, support attach, expansion, and churn create ARR by stream. Sales capacity, developer activation, net retention, and multi-team adoption determine the operating case. ## 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 Apollo's Enterprise Data Graph is a managed GraphQL layer that sits between app teams and backend services. It replaces ad-hoc API integrations and BFF patterns with a single, governed schema ("the Graph") that: - Lets app teams query exactly what they need without knowledge of underlying service topology - Frees backend teams to evolve/replatform services without breaking client contracts - Provides governance, schema management, observability, and usage analytics at enterprise scale Core product lines implied: Enterprise Data Graph (subscription), Freemium (self-serve single-team graphs), Enterprise Support. ## Market No explicit TAM/SAM/SOM figures stated in deck. Demand-side framing offered: - Digital outperformers grow revenue 5x faster, earn 60% higher shareholder returns, and achieve 20% higher operating margins - "A new layer of the Internet that every enterprise will likely adopt" - Apollo GraphQL open-source client reaches ~2.5M weekly npm downloads as of early 2021, up from near-zero in 2016 - Estimated 1.5M active developers on Apollo open-source - 15% attach rate to modern web development (React ecosystem) - 5 years of sustained exponential growth in open-source adoption ## Revenue model Three revenue streams: 1. **Enterprise Data Graph (product subscription)** - primary ARR driver; sold top-down to enterprises via AE+SDR teams 2. **Freemium** - self-serve single-team graphs; PLG motion, developer-led adoption that seeds enterprise pipeline 3. **Enterprise Support** - separate support contracts GTM motion: - Bottom-up: developers self-onboard on freemium; usage signals feed marketing intelligence - Top-down: AE+SDR identifies strategic business buyer at target accounts; converts developer usage into an enterprise-wide graph consolidation deal - New logo ARR target: $XXXk average per new logo - Ramped AE productivity: $2M/year Pricing basis: not explicitly stated; usage-volume (transactions/queries) is the likely expansion driver given the 4.7x first-year usage growth metric. ## Traction & metrics All dollar figures are redacted in the deck (replaced with $XX.XM / $XXXM placeholders). What is confirmed: - **ARR (Q2 2021 forecast):** $XX.XM total ARR (Enterprise Product $XX.XXM + Freemium $X.XXM + Support $X.XXM) - **YoY enterprise ARR growth (20Q1–21Q1):** X.XX×; X.XX× including freemium and support - **ARR target EOY 2023:** $XXXM on ~$XXM total burn - **5 consecutive quarters of increasing ARR growth rate** as of Q2 2021 - **Open-source:** ~1.5M active developers; ~2.5M weekly npm downloads at peak (early 2021) - **Customers:** 3 named (anonymised) enterprise customers cited - top fintech, top travel company, Fortune 500 retailer - **AE productivity:** $2M/year (ramped) Note: COVID-impacted logos in travel and office-sharing were excluded from core metrics. ## Unit economics All specific dollar amounts redacted. Structure is confirmed: **LTV:CAC scenarios (undiscounted, pro forma for 2023 scale):** | Scenario | Lifetime | Avg NRR | LTV:CAC | | -- | -- | -- | -- | | Low | X years | XXX% | X.X | | Mid | X years | XXX% | X.X | | High | XX years | XXX% | X.X | **First Year Cash Flow (per $100k ARR):** - Average first-year prepayment: $XX,XXX - Less: acquisition cost: ($XX,XXX) - Less: cost to serve: ($XX,XXX) - **First year cash flow: $XX,XXX (positive)** **Other confirmed metrics:** - 4.7x average first-year usage growth - NRR first year: XXX% (redacted) - GRR first year: XX% (redacted); rises to XX% with reactivation - Gross margin: XX.X% (redacted) - Cost to acquire $100k new ARR: $XX,XXX (redacted) - Cost to acquire $100k expansion ARR: $XX,XXX (redacted) - LTV:CAC stated as "X-X" range - Cash flow positive in year one of a deal ## Competition / moat No explicit competitive analysis slide. Moat argued through: - 10 years of open-source GTM experience (prior company: Meteor, top-10 GitHub project, 65% EBITDA margin) - 1.5M developers already using Apollo open-source = massive installed base and pipeline - GraphQL standard ownership/stewardship: Apollo co-evolved with GraphQL from 2016 - Network effects: more enterprise graphs → more subgraph contributors → richer shared schema - Governance and schema registry create switching costs once an enterprise standardises Prior failed alternatives cited: API Gateways (operational only) and BFFs (don't scale). ## Team & funding ask / use of funds **Founders:** - Geoff Schmidt - Co-founder & CEO - Matt DeBergalis - Co-founder & CTO - Met at MIT; collaborators for 20 years; previously built Meteor (profitable OSS business) **Exec team:** - John Siebert - CRO (ex-MongoDB, New Relic, Forter) - Eli Staykova - VP Marketing (ex-Cloudflare, Brex) - Parag Sanghavi - VP Customer Success (ex-Databricks, AppDynamics) - Catrina Zhang - CFO (ex-Amazon, Jawbone) - Hatim Shafique - GTM Advisor (ex-Databricks, AppDynamics) **Investors:** Andreessen Horowitz, Matrix (lead investors) --- ## Recommended financial model - **Archetype + why:** SaaS ARR model with PLG/usage-based expansion layer. Apollo has three distinct ARR streams (enterprise product, freemium, support), a PLG funnel driving enterprise pipeline, and unit economics explicitly framed per $100k ARR block - textbook enterprise SaaS with a usage-expansion kicker. - **Forecast horizon & granularity:** Quarterly (Q1–Q4) for Years 1–2 (2021–2022); annual for Years 3–5 (through 2025/2026). EOY 2023 ARR target is the primary management milestone referenced. - **Key drivers & assumptions:** *Revenue build (ARR waterfall):* - Beginning ARR by stream (Enterprise, Freemium, Support) - New logo count per quarter - Average new logo ARR - Expansion rate (NRR – 100%) - GRR / churn - Freemium ARR growth - Support ARR as % of enterprise ARR - AE headcount ramp (key pipeline lever) - AE ramp time to full productivity *Cost structure:* - Gross margin - S&M: AE + SDR costs tied to headcount; CAC per $100k new ARR - R&D: - G&A: - Total burn target: ~$XXM to reach $XXXM ARR *Unit economics inputs:* - First-year prepayment rate - CAC: new logo vs. expansion - LTV: scenario table exists; exact NRR and lifetime inputs redacted - **Scenarios (Base / Bull / Bear - which variables flex):** - Base: AE headcount per deck plan, NRR ~130%, GRR ~87% - Bull: faster AE ramp + NRR >140% (consistent with 4.7x usage growth), freemium attach accelerates - Bear: slower enterprise sales cycles, NRR ~115%, COVID-adjacent verticals remain impaired - **Required sheets / outputs:** 1. `Assumptions` - all inputs, clearly labelled vs 2. `ARR Waterfall` - by stream, quarterly: opening ARR, new logo, expansion, churn, closing ARR 3. `P&L` - revenue, gross profit, S&M / R&D / G&A, EBITDA, net burn 4. `Unit Economics` - CAC, LTV, payback, LTV:CAC by scenario (mirrors slide 17) 5. `Headcount` - AE, SDR, CS, R&D, G&A; drives S&M and R&D cost lines 6. `Cash Flow` - operating + capex + financing; cumulative burn vs. runway 7. `Scenarios` - Base / Bull / Bear toggle feeding ARR Waterfall and P&L 8. `Dashboard` - KPI summary: ARR, NRR, GRR, burn rate, runway, LTV:CAC, new logos added ## Frequently asked questions ### Is the Apollo financial model free? Yes. The Apollo 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.