# Cervest Financial Model

AI-powered Climate Intelligence platform that quantifies physical climate risk at the asset level, delivered as a freemium SaaS product.

- Canonical: https://finamodel.com/startups/cervest
- Excel download: https://finamodel.com/startup-models/cervest.xlsx
- Category: Climate/Energy
- Model type: SaaS ARR / Valuation
- Funding round: Series A
- Funding: $30M
- Founded: 2021
- Geography: Global (US/EU talent base; cervest.earth domain) [DECK, slide 13]
- Customer: B2B

## About the company

Cervest's EarthScan platform uses AI and climate science to score physical climate risk for individual buildings, infrastructure, and portfolios. It covers hazards including flood, heat, drought, water scarcity, and sea-level rise across historical data and long-range scenarios.

EarthScan uses a freemium, self-serve entry point aimed at businesses, financial institutions, and regulators with exposed assets. The deck cites a $40 billion market and a target of 500 million queryable assets, but discloses neither pricing nor current revenue.

Model it as a freemium B2B SaaS funnel: free users or assets convert into paid enterprise accounts with annual contract value, churn, and expansion. An ARR waterfall should feed a P&L and runway plan, with cloud/data costs, the 50-person team, and potential API or data-licensing revenue treated separately.

## 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

- Core product: EarthScan™ - a self-serve, AI/ML-driven platform that scores physical climate risk on individual assets (buildings, infrastructure, portfolios) across multiple risk categories (flooding, extreme temperatures, droughts, sea level rise, heat, water scarcity, air pollution).
- Temporal range: −50 years historical to +80 years forecast climate risk
- Scenarios: 3 climate scenarios - BAU, 2040 emissions peak, Paris-aligned
- Coverage target: 500 million queryable built assets by year end
- Freemium/open access model - free tier plus premium (pricing not disclosed)
- Key differentiators: single source of truth, standardised, asset-centric (not policy/academic), shareable across networks, "always on" continuous learning
- Proprietary "multi-signal" spatio-temporal science framework

## Market

- TAM: $40 billion (described as "untapped")
- No SAM or SOM breakdown provided.
- No growth rate or source citation for the $40B figure given in the deck.
- Context reference: "$trillions in physical assets at risk" (CDP 2019)

## Revenue model

- Freemium model: open/free access tier as acquisition funnel; premium paid tier implied but not named or priced in the deck
- Target customers: businesses, financial services, regulators with physical asset exposure
- Use cases stated: risk discovery, disclosure, strategic growth (visible in product UI)
- No pricing tiers, seat counts, ACV, or contract structure disclosed in deck.
- Channel: self-serve platform (product-led growth implied); partner/customer development function mentioned (Kate Rodger, Head of Customer & Partner Development)

## Traction & metrics

- 500m queryable built assets - target by year end (forward-looking, not current)
- 50 team members
- 40% women
- >200 peer-reviewed papers
- EarthScan™ Early Access Program: Q2 2021
- EarthScan™ full launch: Q3 2021
- No revenue, ARR, customer count, MRR, or growth metrics disclosed.

## Competition / moat

- Slide 9 frames a market evolution: Climate Science (academic/policy) → Climate Data & Analysis (consulting-led, point solutions) → Climate Intelligence (self-serve, automated, networked). Cervest positions itself as the emerging leader of the third era.
- Competitive moat claimed: proprietary spatio-temporal ML framework, open/freemium distribution (first mover), asset-level granularity, network effects from shared standardised data
- No named competitors.
- Market sentiment: "The market is crying out for a category leader" - two external quotes (names/orgs not readable in text extraction)

## Team & funding ask / use of funds

- Funding ask: $30 million Series A
- Key executives:
  - Iggy Bassi - Founder & CEO
  - Dr. Maxime Rischard - Lead Scientist
  - Dr. Benjamin Laken - Head of Innovation
  - Dr. Laura Zamboni - Climate Scientist
  - Sachin Kapila - Chief Climate Risk Officer
  - Partha Bose - Head of Data Strategy
  - Mark Hodgson - Chief Commercial Officer
  - Melissa Ayres - Chief Marketing Officer
  - Kate Rodger - Head of Customer & Partner Development
  - Anna Moses - Head of Operations
- Team composition: 50 people, Silicon Valley + EU, earth sciences / climate / ML / platforms focus

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## Recommended financial model

- **Archetype + why:** SaaS ARR / freemium B2B SaaS model. Cervest is a platform with a freemium acquisition motion converting to paid enterprise/institutional accounts. Revenue is recurring (annual subscriptions or seat-based), making ARR the right unit. Secondary revenue stream (API/data licensing) is plausible but not confirmed.

- **Forecast horizon & granularity:** 5 years (2021–2025), monthly for Year 1 (pre-launch ramp), quarterly thereafter. Series A context warrants visibility through to potential Series B / breakeven.

- **Key drivers & assumptions:**

| Driver | Value |
| -- | -- |
| Launch date | Q3 2021 |
| Addressable built assets at launch | 500m (target) |
| TAM | $40B |
| Free → paid conversion rate | 2–5% |
| Average ACV (paid tier) | $25,000–$100,000 |
| Paid customer target Y1 | 20–50 |
| Gross margin | 70–80% |
| Headcount at raise | 50 |
| Opex burn rate Y1 | ~$10–12M |
| CAC | - |
| LTV:CAC | Target >3x |
| Net revenue retention | 110–120% |
| Churn | <10% annually |
| R&D as % of revenue | 30–40% Y1, declining |

- **Scenarios (Base / Bull / Bear - which variables flex):**
  - **Bear:** Free-to-paid conversion 1%; ACV at low end ($25K); slower enterprise sales cycle; regulatory tailwinds delayed.
  - **Base:** Conversion 3%; ACV $50K; organic PLG + modest enterprise sales team.
  - **Bull:** Conversion 5%; ACV $75K+; regulatory mandates (TCFD, EU SFDR) accelerate demand; data licensing revenue layer added by Year 3.
  - Primary flex variables: conversion rate, ACV, sales cycle length, regulatory pace, cloud infra COGS scaling.

- **Required sheets / outputs:**
  1. Assumptions & toggles (scenario selector)
  2. Monthly cohort model - free signups, conversion to paid, churn, expansion
  3. ARR build (new ARR, churned ARR, expansion ARR, net new ARR)
  4. P&L - Revenue, COGS, Gross Profit, R&D, S&M, G&A, EBITDA, Net Income
  5. Headcount plan (by department)
  6. Cash flow & runway (Series A proceeds vs. burn to Series B)
  7. Unit economics summary (CAC, LTV, payback, LTV:CAC)
  8. Sensitivity table (ACV × conversion rate → ARR at Year 3)
  9. Dashboard / KPI summary

## Frequently asked questions

### Is the Cervest financial model free?

Yes. The Cervest 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.