# Daylight Financial Model

Low-code hyperautomation platform that converts complex enterprise data-collection and workflow processes into guided digital experiences ("Smart Forms"), billed on a metered SaaS basis.

- Canonical: https://finamodel.com/startups/daylight
- Excel download: https://finamodel.com/startup-models/daylight.xlsx
- Category: InsurTech
- Model type: SaaS ARR / Valuation
- Funding round: Series A
- Funding: $123M
- Founded: 2021
- Geography: Canada (all revenue figures in CAD [DECK slide 12]); clients include TD Bank, Allianz Global Assistance, Loblaw/Shoppers Drug, Manulife - primary market is Canadian enterprise.
- Customer: B2B

## About the company

Daylight is a low-code hyperautomation platform that turns complex enterprise data collection and workflow processes into guided smart forms. It sits above legacy systems and integrates with RPA, e-signature, KYC, OCR, and other operational tools.

The company uses metered SaaS: customers pay a base platform subscription and expand as transactions or form submissions grow. It projected ARR growth above 3.3 times and reported 150% retained revenue, with one banking client increasing submissions sharply.

The model is usage-based SaaS ARR. Clients, subscriptions, submissions, unit price, expansion, and churn build revenue. Implementation, workflow adoption, infrastructure costs, and net retention determine the growth and margin outlook.

## 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

- Low-code, business-managed platform to digitise paper-based and legacy enterprise processes into omni-channel smart forms and guided workflows.
- Positions as an outside-in transformation layer sitting above RPA, BPM, eSignature, KYC, OCR, and legacy systems - integrates with all without replacing them.
- Self-service, assisted-channel, and internal (call-centre) deployment modes.
- Key claim: <10% of effort vs traditional development to build solutions.
- Product was formerly branded "FormHero" (visible in slide 8 UI screenshot); rebranded to Daylight Automation Inc.
- Gartner named Hyperautomation its top Strategic Technology Trend for 2020.

## Market

- Total enterprise software dev & maintenance spend: ~$500B/year
- Global market for Hyperautomation Components (USD), source: Grand View Research:

| Segment | 2019 | 2028 (projected) |
| -- | -- | -- |
| Low-Code Application Platforms | $11.4B | ~$60B |
| Robotic Process Automation | $1.4B | ~$10B |
| Digital Experience Platforms | $8.4B | ~$20B |

- Combined addressable hyperautomation components market 2019: ~$21.2B → ~$90B by 2028 (~18% CAGR implied).

## Revenue model

- Metered SaaS: subscription with usage-based overlay ("SaaS with a twist"). Revenue scales with client usage (submissions/transactions) without requiring new contracts.
- Land and expand: initial platform subscription, then organic expansion as client teams build more processes on the platform.
- "Essential Service" stickiness: each deployed process deepens integration and increases switching cost.
- Pricing unit appears to be form submissions / transactions (the banking client chart tracks monthly submissions).
- Direct enterprise sales (no self-serve consumer channel visible in deck).

## Traction & metrics

- ARR growth >3.3x projected for current FY (since March 2020 Seed).
- Retained Revenue (net revenue retention): 150% for 2021FY to date (¾ of year).
- All revenue numbers in CAD.
- Sample banking client: monthly form submissions grew from 7,220 (Apr 2020) to 26,105 projected (Dec 2020) - ~3.6x in 9 months for a single client.
- Named enterprise clients: TD Bank Group, Allianz Global Assistance, Loblaw/Shoppers Drug Mart, Manulife.
- TD Bank - Power of Attorney process: 42 PDFs (EN/FR), 20,000 in-branch sessions, 37,500 person-hours saved/year, ROI on platform subscription in 4 months.
- Allianz Global Assistance - Call Centre Scripting: 8 systems integrated, 83% reduction in training (5 weeks fewer), 30% reduction in average call time.
- Loblaw/Shoppers Drug - Flu Shot Administration: 6 weeks client-request-to-live, 1.5M+ transactions in first 2 months, ~2,500 stores, no training required.
- Real Estate MLV case study: 28 minutes of client-time reduced per interaction, 100% reduction in discrepancies, 50,000 person-hours saved/year, 3-week build & QA.
- Outside Financial Institution Transfers case study: 36 PDFs (EN/FR), 100% reduction in training, 88% reduction in errors, 4-week build & QA.

## Unit economics

- Net Revenue Retention: 150% - strong NRR confirms land-and-expand working.
- Payback (at client level): TD Bank case shows ROI on platform subscription in 4 months.

## Competition / moat

- Competitive context named: RPA vendors (UiPath, Blue Prism class), BPM/workflow tools, UX/experience platforms - all characterised as costly, complex, and slow-to-deploy.
- Moat described as:
  - Low-code / business-managed: non-IT users can build and own processes.
  - Complementary/targeted: sits on top of existing tech stack rather than replacing it, reducing displacement risk.
  - Each project increases stickiness (cited explicitly).
  - 150% NRR evidences expansion moat in practice.

## Team & funding ask / use of funds

- Ryan Kimber - CEO; formerly CTO and Chief Innovation Officer at Think Research.
- Art Harrison - CGO (Chief Growth Officer); formerly VP Marketing & Communications at Interfaceware.
- Natasha Lala - COO; formerly COO at ApplePie Capital, Chief of Staff and VP Engineering at OANDA.
- Seed round: March 2020, led by Golden Ventures, Bessemer Venture Partners participating.

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## Recommended financial model

- **Archetype + why:** Usage-based / metered SaaS ARR model. Revenue has two components: (1) a base platform subscription per client, and (2) a variable usage charge that scales with submission/transaction volume. The 150% NRR and the per-client submission growth chart (7,220 → 26,000+ in one year for one banking client) confirm that volume expansion within accounts is the primary growth driver - a pure ARR seat model would obscure this. A 3-statement model underneath is needed to size cash needs for the raise.

- **Forecast horizon & granularity:** Monthly for Year 1–2, quarterly for Year 3–5. Deck is Canadian-dollar-denominated; model in CAD.

- **Key drivers & assumptions:**

| Driver | Value / source |
| -- | -- |
| Starting ARR (base year) | Unknown - not disclosed |
| ARR growth rate (FY in progress) | >3.3x vs prior year |
| Net Revenue Retention | 150% |
| New logo adds per year | Unknown |
| Average contract value (new logo) | Unknown |
| Usage uplift per client per year | ~3x in Year 1 (banking client datapoint) |
| Gross margin | Unknown |
| Sales cycle | Unknown |
| COGS (hosting + support) | Unknown |
| Headcount / opex | Unknown |
| CAD/USD FX | At par or with explicit assumption |

- **Scenarios (Base / Bull / Bear - which variables flex):**
  - **Bull:** NRR holds at 150%+, 6+ new logos/year, usage ramp mirrors banking client (3x in Year 1). ARR reaches 10x+ in 3 years.
  - **Base:** NRR moderates to 120–130%, 3–4 new logos/year, usage growth 1.5–2x after Year 1. ARR ~5–7x in 3 years.
  - **Bear:** NRR falls to 100–110% (expansion slows), new logo adds delayed by longer sales cycles, 1–2 new logos/year. Cash burn accelerates.
  - Flex variables: NRR, new logo count, ACV, usage ramp per client, gross margin, time-to-expand per client.

- **Required sheets / outputs:**
  1. **Assumptions** - all drivers in one place, clearly tagged DECK vs ASSUMED.
  2. **ARR Bridge** - new ARR, expansion ARR (usage uplift), churn/contraction, ending ARR by period.
  3. **Revenue Schedule** - subscription base + metered usage split per cohort of clients.
  4. **Client Cohort Model** - track each logo class: initial ACV, expansion curve, NRR by vintage.
  5. **P&L (Income Statement)** - revenue, COGS, gross profit, S&M, R&D, G&A, EBITDA.
  6. **Cash Flow & Runway** - monthly burn, ending cash, implied runway; size against raise proceeds.
  7. **Balance Sheet** - simplified; required for 3-statement close.
  8. **KPI Dashboard** - ARR, NRR, LTV/CAC (once data supplied), gross margin %, Rule of 40.
  9. **Scenarios tab** - toggle Base/Bull/Bear via a single input cell.

## Frequently asked questions

### Is the Daylight financial model free?

Yes. The Daylight 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.