# CGHero Financial Model Two-sided talent marketplace connecting CGI, 3D, and VFX artists ("Heroes") with studios and production companies worldwide. - Canonical: https://finamodel.com/startups/cghero - Excel download: https://finamodel.com/startup-models/cghero.xlsx - Category: Marketplace - Model type: Marketplace / GMV - Funding round: N/A - Funding: $4M - Founded: 2022 - Geography: Global; UK-founded (Manchester); 100+ countries on supply side - Customer: B2C ## About the company CGHero is a talent marketplace for CGI, 3D, and VFX work, connecting production studios with vetted artists worldwide. It supports individual freelance engagements as well as managed outsourcing, co-development, and larger distributed production teams. The platform reported 5,500 registered artists, 400 studio clients, 1,000 completed productions, and talent in 100 countries. This gives CGHero a two-sided marketplace foundation, while its managed-service tiers address projects that need more coordination than a simple freelancer match. The model separates marketplace commission from managed-service gross profit. Active studio clients, projects per client, artist matching, average project value, and take rate drive marketplace revenue; higher-touch tiers add studio billing less artist delivery cost. Supply growth, repeat studios, project mix, and service margin are the key forecasting levers. ## 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 CGHERO is a collaborative talent platform enabling production companies to source and manage CGI, 3D, and VFX talent at any scale - from individual freelancers to fully distributed "Liquid Super Teams." The platform addresses a supply/demand mismatch: complex CGI/VFX productions have outpaced studios' ability to hire in-house, while thousands of skilled artists globally lack a structured route to work. Studios get flexible, pre-vetted, production-ready talent; artists get access to professional productions they couldn't reach independently. Service tiers (roadmap shown on slide 7, 2019–2023): Internal Hires → Freelance & Contract → Managed Outsource → Co-dev Studio → Liquid Super Teams ## Market - TAM: $270bn global studio market - SAM (CGHERO opportunity - "value of non-core outsource production"): $8bn total across five verticals: - Gaming: $2.1bn - TV & Film: $3.3bn - Retail: $1.6bn - Automotive: $0.8bn - Architecture: $0.3bn - Market growth rate: Described as "high growth" but no CAGR cited ## Revenue model Not explicitly stated in deck. Based on platform description and service tiers, the model is likely one or more of: - Take-rate / commission on freelance placements (marketplace fee on artist earnings or studio billing) - Managed-service margin on outsourced production (studio-side billing with artist cost underneath) - Subscription or platform-access fee No pricing page, take-rate %, or revenue recognition detail shown. ## Traction & metrics All from slides 05 and 06: - 5,500 Industry Heroes (supply side, registered artists) - 400 Studio Clients (demand side) - 1,000 Productions completed - 100 countries represented in artist supply base - Founded 2017 - No revenue figures, GMV, growth rates, or cohort data shown ## Competition / moat Not explicitly framed as a competition slide in the deck. Implied moat: - Supply-side network of 5,500 vetted, production-ready artists across 100 countries - Founder's prior domain experience: Jonathan Lloyd founded Falling Pixel (3D marketplace, acquired by TurboSquid/Intel/Kodak-backed in 2011) and served as VP Strategic & Product Development at TurboSquid - Positioned as managed/curated supply rather than open freelance marketplace (quality and vetting angle implied) - Epic MegaGrants recipient - signals platform/tech credibility in the gaming/3D space ## Team & funding ask / use of funds Team: - Jonathan Lloyd - Founder/CEO (implied); previously Falling Pixel → TurboSquid - Chris Lawrence - COO; formerly Falling Pixel, Burrows CGI; Computer Animation BSc - Paul Bannon - Producer; formerly Dock10, Futureworks, Travellers Tales, EON Reality, Ripstone; Game Design BA - Jonathan Webb - CTO; formerly Playtech, BAE Systems, Barclaycard; Game Design BSc Board / advisors: - Ron Ashtiani - Angel; Founder of Atomhawk Design (sold to Sumogroup Plc); credits include EA, Microsoft, Warner Bros. - Eyal Malinger - Board; Investment Director, Partner at Beringea; board memberships at Papier, CreativeX, Commonplace, Festicket, Poq; Harvard MBA - Paul Drew - NXD; SVP Metaswitch Networks; angel investor in marketplace-focused tech companies; Oxford MSc Investors: - Beringea (institutional VC) - Fuel Ventures - Epic MegaGrants (non-dilutive grant from Epic Games) - Additional industry angels --- ## Recommended financial model - **Archetype + why:** Marketplace GMV / take-rate model, layered with a managed-services P&L for the higher-tier offerings (Managed Outsource, Co-dev Studio, Liquid Super Teams). Two-sided marketplace dynamics (supply growth, demand growth, match rate, take-rate) drive top-line; managed-service tiers carry a separate gross margin profile (billing rate minus artist cost). A pure SaaS model is not appropriate - no subscription pricing evidence. An agency/services P&L alone understates the platform scalability angle. - **Forecast horizon & granularity:** 5-year (annual columns, monthly for Year 1 if runway/cash-burn is in scope). Given early traction and no revenue disclosed, a monthly build for Y1 is valuable for burn visibility. - **Key drivers & assumptions:** - Number of active studio clients (demand side): 400 current; growth rate 30–50% YoY for Y1–Y3, moderating to 20% Y4–Y5, given early-stage network effects - Productions per client per year: 2–4 productions/client/year; increases as managed-service tiers deepen - Average production value (APV) / GMV per production: £15k–£50k depending on tier (freelance vs. managed outsource); no deck data - Take-rate (marketplace fee): 15–25% of GMV for freelance/contract tier; managed-service tiers carry ~40–50% gross margin (studio billing minus artist cost) - Artist supply (Heroes): 5,500; growth tracks demand with lag; key constraint is vetted-supply bottleneck - Revenue mix by tier: majority currently freelance/contract (lower margin); shift toward managed outsource / co-dev by Y3 per roadmap - Gross margin: 20–30% blended (lower for managed services with artist pass-through cost; higher for pure platform/matching revenue) - Headcount/opex: small team (~10–20 FTE); no data in deck - build bottoms-up with sales, ops, tech functions - Geographic mix: predominantly UK/EU near-term; global supply already in place - **Scenarios (Base / Bull / Bear - which variables flex):** - Base: 30% client growth, 2.5 productions/client, £20k APV, 20% take-rate - Bull: 50% client growth, higher APV via managed-service upsell, faster tier migration, 25% take-rate on platform tiers - Bear: 15% client growth, stagnation in managed-service adoption, take-rate compression from competition, higher artist acquisition cost - **Required sheets / outputs:** 1. Assumptions dashboard (all drivers in one place) 2. Supply-side build: Hero count growth, vetting cost, activation rate 3. Demand-side build: Studio client adds, production volume per client, tier mix 4. GMV bridge: Productions × APV per tier 5. Revenue & gross profit: Take-rate revenue (marketplace) + managed-service margin 6. P&L: Revenue → gross profit → operating expenses → EBITDA 7. Headcount plan 8. Cash flow / runway (burn rate, months of runway) 9. Scenario toggle 10. KPI summary: Clients, productions, GMV, revenue, gross margin %, burn, runway ## Frequently asked questions ### Is the CGHero financial model free? Yes. The CGHero 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.