# Limitless Financial Model B2B SaaS platform enabling enterprises to crowdsource customer service to a qualified gig workforce ("Experts"), augmented by AI automation. - Canonical: https://finamodel.com/startups/limitless - Excel download: https://finamodel.com/startup-models/limitless.xlsx - Category: AI/ML - Model type: SaaS ARR / Valuation - Funding round: Series B - Funding: $10M - Founded: 2021 - Geography: US and Rest of World; live in 22 countries as of deck date [DECK slide 7]. - Customer: B2B ## About the company Limitless operates a Gig Customer Experience platform that combines AI with a crowd of vetted customer-service Experts. It helps enterprise clients resolve customer questions through qualified people, automation, and a SmartCrowd workflow rather than relying entirely on in-house or outsourced call centres. The company is live in 22 countries and sells a hybrid commercial model: an annual platform subscription plus consumption revenue per resolved ticket, subject to minimum commitments. Its AI learns from Expert interactions, while ticket volume and Expert payouts determine the variable side of unit economics. The model uses client cohorts, subscription fees, ticket volumes, and revenue per resolution to build revenue. It forecasts Expert payouts, automation rates, platform hosting, gross margin, channel and direct sales capacity, operating headcount, cash burn, and runway across geographic expansion scenarios. ## 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: SmartCrowd™ - routes support tickets to vetted "Expert" gig workers (brand product users) who resolve queries on-demand. Two AI modules: - SmartAssist: suggests responses to Experts, who personalise and train the AI. - SmartAnswer: automates low-value, repetitive queries based on Expert-trained models. Value prop to enterprise clients: eliminate high attrition (50%+/yr), absenteeism (6–8% daily), slow response times (4h+ on messaging), and poor FCR (70–80%) inherent in traditional call centres, at lower cost via gig supply. ## Market - TAM: 265 billion customer service interactions/year at $1 trillion total cost (IBM). - SAM: Contact Centre Outsourcing (CCO) market $105 billion by 2023 (Everest Group). - SOM: GigCX-addressable slice of CCO estimated at >20% of CCO = ~$20 billion by 2021E (Everest Group). - Macro tailwind: US gig workforce growing from 57M (2017) to projected 83M (2027); permanent workforce shrinking from 103M to 86M over same period. ## Revenue model - Contracting: annual subscription to access the platform. - Pricing: per-resolved-ticket; clients commit to a minimum revenue guarantee or pre-purchase credits. - Channels: direct sales & client success (2020–2021); BPO and CX tech channel partners planned (2021–2023). - Target verticals: Technology Marketplaces, New Media. - Geographic mix: shifted from 53% US / 47% RoW in 2019 to 32% US / 68% RoW in 2020. ## Traction & metrics - Live in 22 countries; 9 more countries coming online H1-2020. - Named clients include brands in technology and media segments (iZoom shown in product demo). - Past clients / validation: Unilever, Microsoft, Sky, Vodafone (founders' prior BPO business, not Limitless clients). - No explicit revenue figure, ARR, customer count, or ticket volume disclosed in the deck. ## Competition / moat Competitive positioning shown on a Quality vs. Cost matrix: - GigCX + AI positioned as high engagement quality at low cost - outflanking all alternatives. - Alternatives named: In-house call centres (high quality, high cost), onshore/offshore outsourced contact centres (mid quality, variable cost), WFH agents, communities (low cost, low quality), self-service / bots / VAs (low cost, low quality). - Moat levers: proprietary SmartCrowd platform (multi-award winning per deck); AI trained on Expert interactions creates a data flywheel; network of vetted Experts is supply-side defensibility; 22-country footprint with rapid onboarding. ## Team & funding ask / use of funds Team: - Roger Beadle - CEO; 20+ years CX SaaS & BPO. - Megan Neale - COO; 25 years managing large-scale customer service operations. - Jim Cozens - Head of Engineering; 25 years enterprise CX software. - Founding team previously ran one of Europe's largest CX outsourcers (2,000+ staff, clients incl. Unilever, Microsoft, Sky, Vodafone); sold to Hinduja Group. --- ## Recommended financial model - **Archetype + why:** B2B SaaS / usage-based hybrid. Revenue has two components - (1) annual subscription platform fee and (2) per-resolved-ticket consumption revenue with a minimum commitment floor. This is structurally similar to a usage-based SaaS model (think Twilio / Zendesk), where ARR from subscriptions provides a floor and ticket volume drives upside. Build as a customer-cohort model tracking clients, avg tickets/client/month, and revenue per ticket. - **Forecast horizon & granularity:** Monthly for Years 1–2 (2021–2022), quarterly for Years 3–5 (2023–2025). Five-year horizon appropriate for a growth-stage B2B SaaS raising. - **Key drivers & assumptions:** - New enterprise client adds per month - Average annual subscription fee per client - Average monthly ticket volume per client - Revenue per resolved ticket - Minimum revenue commitment as % of contracted ticket volume - Expert payout per resolved ticket - Gross margin - Revenue geographic mix: US 32%, RoW 68% in 2020; - Churn / logo retention - AI automation rate ramp - Sales headcount & AE quota - **Scenarios (Base / Bull / Bear - which variables flex):** - Bear: slow enterprise sales cycle, 1 new client/month, low ticket volumes, high Expert payout rate, US market penetration slow. - Base: 2 new clients/month, mid-range ticket volumes, 50% gross margin, AI automation ramp per plan. - Bull: channel partner acceleration (BPO partners per 2021–2023 roadmap), 4+ clients/month, ticket volumes at high end, AI automation reduces unit COGS faster. - **Required sheets / outputs:** 1. Assumptions dashboard (all drivers, tagged) 2. Client cohort build (new logos, retained logos, churned) 3. Revenue build (subscription + ticket consumption, by cohort) 4. COGS build (Expert payouts, platform hosting, support) 5. Gross profit & gross margin % 6. OpEx (S&M, R&D, G&A) - headcount-driven 7. EBITDA / operating loss 8. Cash & runway (simplified cash flow) 9. KPI dashboard: ARR, net revenue retention, tickets processed, revenue per ticket, automation % ## Frequently asked questions ### Is the Limitless financial model free? Yes. The Limitless 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.