KA

KarmaCheck Financial Model

• Background screening platform targeting hyper-growth companies and high-velocity hiring.
• "Best-in-class" tech stack vs. legacy incumbents - positions on speed (fast-to-instant checks), mobile-first UX, and candidate transparency.
• Single API covers: criminal/occupational health screenings (OHS), Identity Verification (IDV), Motor Vehicle Records (MVR), licenses, credit checks, social media checks, and self-pay.
• Industry-first subscription packaging (all competitors are pay-as-you-go).
• Self-serve onboarding with instant account provisioning (vs. several days for competitors).

• Background Screenings TAM: $13B (long-term); current market spend: $6B; 56M checks/year.
• $7B whitespace attributed to new products, services, and international.
• Long-term CAGR: 6%.
• Consumer Identity Access Management (CIAM) adjacent TAM: $23B; current spend: $7B; CAGR 14.9% until 2025.
• Gig economy gross volume: $297B (2020) → $455B (2023); 14.4% CAGR.
• 25–30% of US workforce are contingent workers.
• SAM and SOM not broken out in deck.

• Primary: SaaS subscriptions - recurring packages of background checks; unused checks from subscriptions retain healthy margins.
• Secondary: Pay-as-you-go - per-check transactional; serves as upsell pipeline into subscriptions.
• Pricing strategy: 20%+ cheaper than incumbents from existing automations; 40–50% cheaper in self-serve funnel.
• Go-to-market: three pillars - SaaS subscriptions, aggressive pricing, self-serve funnel.
• Self-serve funnel targets SMB/mid-market; enterprise acquired via sales motion (3-month sales cycle).
• "Data Re-Use" strategy: customer data accumulation creates compounding cost advantage over time.

• Annual run rate: $2M.
• Run rate trajectory (from chart): ~$0 at Q2 2020 → ~$50K at Q3 2020 → ~$550K at Q4 2020 → ~$800K at Q1 2021 → ~$1.2M at Q2 2021 (chart y-axis max = $1.2M, but headline states $2M ARR - likely reflects post-Q2 momentum or annualized MRR).
• Net revenue retention: 179%.
• Screenings completed: 125K+.
• Customers: 100+.
• Sales cycle: 3 months.
• Revenue growth rate not stated explicitly; implied very high given near-zero start Q2 2020 → $2M ARR by mid-2021.

• CAC: $113 (self-serve funnel).
• LTV: $563.
• LTV:CAC ratio: 5.6x.
• Gross margins: 65%.
• Payback to profits: 14–16 months based on CAC.
• Note: The $113 CAC and $563 LTV appear to be self-serve segment figures. Enterprise/subscription segment economics not separately disclosed. The 5.6x LTV:CAC shown on slide 13 may blend segments.

Competitors identified: | Company | Stage | Valuation | Revenue | Revenue Model | | -- | -- | -- | -- | -- | | Vetty | Seed | $20M | - | Pay-as-you-go | | Checkr | Pre-IPO (Accel) | $4.6B | $220M (est.) | Pay-as-you-go | | Certn | Series A+ | $115M | $8M | Pay-as-you-go | | Truework | Series B (Sequoia) | $150M (est.) | $3M (est.) | Pay-as-you-go | | HireRight | Privately-owned | $2.65B (est.) | $482.5M | Pay-as-you-go | | First Advantage | Public | $2.96B | $530.4M | Pay-as-you-go | | Sterling | PE-owned / Pre-IPO (Goldman) | $7.7B (est.) | $1.4B | Pay-as-you-go |

• Moat claims: industry-first subscription model; data re-use flywheel; instant provisioning; single-API breadth; 179% NRR (expansion revenue from existing customers).
• All named competitors operate pay-as-you-go only.

• Eric Ly - CEO & Co-Founder; LinkedIn Co-Founder.
• Mark Lieberwitz - CPO & Co-Founder; ex-Meltwater, 15-year product lead.
• Shaunak Mali - VP Special Projects & Co-Founder; original architect at Checkr, worked on Uber relationship.
• Tim Flanders - VP Engineering, Founding Team; ex-Chordiant, 25+ years enterprise software.
• Bo Mohazzabi - Head of Sales & Customer Success; ex-Amplitude, 12+ years SaaS/growth.
• Prior funding: Not explicitly stated; "Seed" stage implied relative to competitors listed.

• Archetype + why: SaaS ARR model with dual-stream revenue (subscription MRR + transactional PAYG). The 179% NRR, LTV/CAC framing, subscription focus, and self-serve + enterprise motion all point to a classic SaaS ARR build. PAYG checks are a secondary transactional line that feeds the subscription upsell pipeline.
• Forecast horizon & granularity: 3 years (2021–2024); monthly for Year 1, quarterly for Years 2–3.
• Key drivers & assumptions:
• ARR starting point: $2M.
• Customer count: 100+ at deck date; split into self-serve (SMB) and enterprise segments.
• Self-serve CAC: $113.
• Enterprise sales cycle: 3 months.
• LTV: $563 (self-serve); enterprise LTV higher.
• LTV:CAC ratio: 5.6x.
• Gross margin: 65%.
• Net revenue retention: 179% - drives expansion MRR from existing customers; key upside lever.
• New logo adds per month (self-serve):.
• New logo adds per month (enterprise):.
• PAYG revenue mix:.
• Average subscription ACV:.
• CAC payback period: 14–16 months.
• S&M spend as % of revenue:.
• Headcount growth:.
• Gross check cost / data re-use savings: 20%+ from automations currently; assumed to improve as data re-use scales.
• Scenarios (Base / Bull / Bear - which variables flex):
• Base: NRR stays ~150% (some churn at lower end), self-serve CAC stable at $113, 65% gross margin.
• Bull: NRR maintains 179%, gross margin improves to 70%+ via data re-use, self-serve funnel scales >40–50% cheaper per.
• Bear: NRR compresses to 120% (competitive pressure from Checkr/others), enterprise sales cycle lengthens, gross margin stays flat at 65%.
• Required sheets / outputs:

1. Assumptions - all drivers in one place.
2. Revenue - MRR bridge: new logos × ACV + NRR expansion + churn; split self-serve vs. enterprise; PAYG transactional line.
3. Unit Economics - CAC, LTV, payback by segment; cohort expansion table (179% NRR).
4. P&L - Revenue, COGS (gross margin), S&M (growth loop spend), R&D, G&A, EBITDA.
5. Headcount - by department, feeding into opex.
6. Cash / Runway - given no funding ask disclosed, model cash burn vs. ARR growth to show when self-funded.
7. KPI Summary - ARR, NRR, LTV:CAC, gross margin, CAC payback, customer count.