Axle Health Financial Model

Three core modules:

1. AI Scheduling - assigns best clinician, day, and time per patient; office-driven or clinician-driven; continuity-of-care prioritization.
2. Workforce Management - headcount demand forecasting by geography and time period; real-time utilization projections.
3. AI Patient Engagement - automated visit confirmation, reminder, and ETA texts/calls; detects mobile vs landline and routes accordingly.

Supporting capabilities: route optimization (proprietary home health logistics algorithms), advanced analytics (heatmaps, custom reporting, no-show rate, mileage by clinician), white-glove onboarding with dedicated implementation manager.

EMR integration via bidirectional read/write (reads orders/demographics, writes appointment assignments back); integration with HCHB specifically called out. RPA used for EMR integrations where API unavailable.

• Home health market size: ~$150B today, growing at ~8% CAGR, projected ~$230–240B by 2030.
• Demand driver: 65+ population growing 27% by 2040; 88% of seniors prefer aging in place.
• Labor constraint: Industry was 25% undersupplied before COVID; gap projected to reach 33% by 2030 (clinician supply growing ~1% CAGR vs revenue growing ~8% CAGR).
• Non-clinical labor waste: Providers spend $45B on labor for non-clinical activities; clinicians spend less than half their workday with patients (~3 of ~9 hours).

• Business model: B2B SaaS sold to home health and hospice agencies.
• Pricing: Not in deck. No ACV, per-clinician seat, per-visit, or per-agency pricing disclosed.
• Channels: Direct sales implied (dedicated implementation manager, enterprise onboarding process).

• NRR: 121% annual
• Cohort 1 at period 5: 122%
• Cohort 2 at period 4: 117%
• Cohort 3 at period 3: 110%
• Cohort 4 at period 2: 103%
• 5 cohorts shown total
• Cohort period unit: Not labeled (likely quarters or months - "annual NRR" headline with 5 periods suggests likely quarters).

ROI metrics delivered to customers:

• +17% increase in clinician productivity
• -55% decrease in patient missed visits
• -32% decrease in mileage costs
• Customer EBITDA impact: +8.5% EBITDA increase, +7% revenue increase, +1% additional EBITDA
• Note: the deck shows two separate "Increase in EBITDA" rows (+8.5% and +1%) - likely productivity gain vs mileage savings decomposed separately.

• Axle positioned as "the most advanced field operations product on the market".
• Competitive moat sources:
• Proprietary home health logistics / routing algorithms
• Deep EMR integrations (bidirectional, HCHB cited)
• AI scheduling that writes back into EMR (vs manual or scheduler-only tools)
• High switching cost: white-glove onboarding, workflow mapping, trained staff
• No direct competitor named in deck. "We've looked at a lot of home health scheduling tools" quote implies multiple alternatives exist.
• Why now: CURES Act interoperability regs enable modular product strategy; rising labor gap increases provider desperation; AI advances unlock new scheduling logic and RPA-based EMR integrations.

Team:

• Prior employer logos: Uber, Apple, Amazon, Google, Microsoft, Salesforce, Intuit, IBM, Heal, Komodo Health, Philips Healthcare, Kaiser Permanente, Mass General Brigham, Mount Sinai, Evernorth.
• Academic backgrounds: Yale, Harvard, Stanford, MIT, Columbia, Penn, Cornell, Northwestern, Johns Hopkins, U Chicago, USC, U Michigan.
• Individual names/titles: Not shown.

Investors: Y Combinator, Pear, TRAC AI/VC, Pioneer, Soma Capital.

Funding ask:

• Round: $10M Series A
• Use of funds:
• R&D: $7M (70%)
• S&M: $2M (20%)
• G&A: $1M (10%)

Archetype + why: B2B SaaS ARR model. Revenue is recurring software subscription sold to home health agencies. Expansion NRR of 121% is the central mechanic - new logo acquisition plus upsell/seat expansion drives ARR compounding. Standard SaaS ARR waterfall (new ARR, expansion ARR, churned ARR) is the right frame.

Forecast horizon & granularity:

• 3-year forecast (Year 1–3 from Series A close), monthly for Year 1, quarterly for Years 2–3.
• Rationale: Series A with R&D-heavy spend profile ($7M of $10M) suggests 18–24 months to meaningful revenue scale; 3-year horizon captures path to Series B metrics.

Key drivers & assumptions:

*Revenue / ARR:*

• Starting ARR: ~$500K–$1.5M implied by 5 visible cohorts and expansion ratios, but no number in deck. Must confirm with company. Model placeholder: $750K ARR at Series A close.
• ACV per agency: $30K–$80K/year (typical vertical SaaS for mid-market healthcare agencies). No pricing in deck. Sensitivity driver.
• New logos per quarter: 2–5 agencies/quarter in Year 1, ramping with S&M spend ($2M budgeted = ~2 quota-carrying reps at $150K OTE).
• Net Revenue Retention: 121%. Use as base case; expansion mechanism is likely seat/clinician count or branch adds.
• Gross Revenue Churn: ~5–8%/year (implied by NRR >120% with some churn; healthcare agencies have sticky workflows post-onboarding).

*Cost structure:*

• R&D spend: $7M of $10M raise deployed over ~18–24 months.
• S&M spend: $2M over ~18–24 months.
• G&A spend: $1M over ~18–24 months.
• Gross margin: 65–75% (vertical SaaS with implementation services component; white-glove onboarding may weigh on gross margin initially).
• COGS includes: implementation manager labor, customer success, hosting/infrastructure.

*Headcount:*

• S&M headcount: 2–3 AEs + 1 SDR in Year 1, given $2M budget.
• R&D headcount: 6–10 engineers/PMs given $7M budget.
• CS/Implementation: 1–2 dedicated implementation managers per 8–12 active customers (based on onboarding process described in slide 13).

Scenarios (Base / Bull / Bear):

Required sheets / outputs:

1. ARR Waterfall - Beginning ARR, New ARR, Expansion ARR, Churned ARR, Ending ARR (monthly Yr 1, quarterly Yr 2–3)
2. Income Statement - Revenue, COGS, Gross Profit, S&M, R&D, G&A, EBITDA, Net Income
3. Cash Flow & Runway - Monthly cash burn, cash balance, months of runway from $10M raise
4. Cohort Model - NRR by cohort to validate 121% assumption and project expansion revenue
5. Headcount Plan - Hires by function by quarter, fully-loaded costs
6. Unit Economics Dashboard - CAC (once sales data available), LTV, LTV/CAC, payback period, magic number
7. Scenario Toggle - Single input sheet driving Base/Bull/Bear outputs