# The Atlas Financial Model Free online community for city officials that monetises by selling govtech vendors access to that audience - Canonical: https://finamodel.com/startups/the-atlas - Excel download: https://finamodel.com/startup-models/the-atlas.xlsx - Category: Marketplace - Model type: Marketplace / GMV - Funding round: Pre-Seed - Founded: 2019 - Geography: US (City of San Diego, City of Los Angeles referenced; North America implied by logo) [DECK] - Customer: B2B ## About the company The Atlas is a free online community where city officials discover case studies, follow issues, and ask peers about government solutions. It addresses a fragmented procurement and knowledge-discovery process by organizing a focused audience for civic and government technology. The platform had 12,000 city users in less than a year and generated $300,000 of ARR from vendors seeking access to that audience. Its next phase is a marketplace where vendors can list solutions and city governments can request information or transact directly. The model begins with vendor subscription and sponsorship ARR. Paying vendors, contract value, renewal, and city-user growth determine the current business, while vendor listings, buyer intent, transaction value, and take rate can add marketplace revenue later. Audience engagement, vendor retention, sales-cycle reduction, and marketplace activation are the key drivers. ## 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 - Free platform where city officials browse case studies, follow topics, and post questions - Solves the problem that government officials have no structured way to discover solutions - forced to use Pinterest, conference booths, cold emails - "What we're building next": a marketplace layer where vendors can list products and city governments can transact directly (e.g. "Buy Now" / "Request More Info" for a Siemens stormwater product) ## Market - TAM: $1.6 trillion in annual local government spending (US cities) - Categories of spend shown: wastewater, air quality, drinking water, solid waste, noise pollution, energy management ## Revenue model - Current: B2B SaaS / sponsorship sold to companies (govtech vendors) who want access to the city-official audience; reported as ARR - Next phase: Marketplace / transactional layer - vendors list products, cities buy or request info directly through The Atlas - City-side is free (supply-side subsidy model, analogous to a B2B media/marketplace) - Pricing per contract not disclosed in deck ## Traction & metrics - 12,000 city users on the platform, achieved in <1 year - $300K ARR from paying company (vendor) customers - 66% decrease in B2G (business-to-government) sales cycle for vendor customers - No revenue growth rate or cohort data shown ## Competition / moat - Moat framing: incumbents are conferences, cold email, and ad-hoc discovery (Pinterest cited) - no direct competitor named - Network effect implied: more city users → more valuable to vendors → more vendor revenue funds platform growth - No competitive matrix shown ## Team & funding ask / use of funds - CEO: Elle Hempen - 5 years government experience, former city consultant, UCLA MBA - COO: 5 years government experience, former city consultant, Rice University Civil Engineer - CTO: Former Recovery Brands, full-stack engineer / data architect - Advisors / affiliations: White House OSTP, EPA, City of London --- ## Recommended financial model - **Archetype + why:** B2B SaaS / marketplace hybrid ARR model. Revenue is currently subscription/sponsorship ARR from govtech vendors (supply-side free, demand-side paid). The "next" product is a transactional marketplace. Model should support both revenue streams: (1) vendor subscription/sponsorship ARR, (2) marketplace GMV with take-rate. - **Forecast horizon & granularity:** 3 years monthly (Year 1–2 monthly, Year 3 quarterly roll-up). Company is pre-Series A with <1 year of ARR history - monthly granularity is essential to track ramp. - **Key drivers & assumptions:** *Supply side (city users - free):* - City user base: 12,000; monthly new user growth rate *Demand side (paying vendors - ARR):* - Number of paying vendor accounts: implied ~$300K ARR / unknown ACV - Net new vendor logos per month - Annual contract value (ACV) per vendor - Logo churn rate - Expansion / upsell rate *Marketplace (next phase):* - GMV per transaction - Take rate - Launch quarter *Cost structure:* - Headcount: 3 co-founders confirmed; additional hires - COGS (hosting, infrastructure) - S&M spend (govtech conference sponsorships, content) - R&D (engineering for marketplace build) - **Scenarios (Base / Bull / Bear - which variables flex):** - Bear: vendor ACV stays low ($10K), churn 20%, marketplace delayed 12 months - Base: vendor ACV ~$15–20K, churn ~12%, marketplace live in 6–9 months, moderate GMV ramp - Bull: vendor ACV expands to $30K+, marketplace take-rate revenue matches subscription ARR by Y3, city user growth accelerates via partnerships - **Required sheets / outputs:** 1. Assumptions - all drivers in one place with scenario toggle 2. City User Growth - monthly free-side supply funnel 3. Vendor ARR - logo count × ACV, MRR bridge (new + expansion − churn) 4. Marketplace GMV & Revenue - GMV, take-rate revenue (activate once launched) 5. P&L - blended revenue, COGS, gross profit, OpEx by category, EBITDA 6. Headcount plan - by function, tied to OpEx 7. Cash & Runway - burn, cash balance, months of runway (critical for fundraise context) 8. KPI Dashboard - ARR, city users, vendor count, NRR, CAC payback, gross margin ## Frequently asked questions ### Is the The Atlas financial model free? Yes. The The Atlas 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.