DADaylight Financial Model
InsurTech Startup Financials (Free Excel Download)
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.
professionals from Deloitte
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About this model
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.
A turnkey financial model
Live formulas, no hardcoded values
Outputs are driven by live formulas, so the workbook updates from its assumptions instead of relying on hardcoded results.
All assumptions in one tab
Inputs are clearly marked in the Assumptions tab and separated from calculations, making it clear what to change and what to leave intact.
Statements always balancing
For integrated-statement models, the balance sheet, cash flow, and supporting schedules tie through properly.
Distinct schedules for clarity
Debt, working capital, taxes, and cash flow can get messy quickly. We group calculations in clear schedules, not across disconnected tabs.
No hidden macros or external links
There are no unexplained external workbook links or macros to undermine auditability or portability.
Changes flow through the model
Update a key driver and see the impact carry through the forecast, financing, and return outputs. We never use hardcoded numbers in formulas.
About Daylight
meetdaylight.com
How to build a detailed financial model for Daylight
A complete walkthrough of the business, drivers, and assumptions behind the downloadable Daylight model - distilled from its pitch deck and publicly available information.
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.
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:
- Assumptions - all drivers in one place, clearly tagged DECK vs ASSUMED.
- ARR Bridge - new ARR, expansion ARR (usage uplift), churn/contraction, ending ARR by period.
- Revenue Schedule - subscription base + metered usage split per cohort of clients.
- Client Cohort Model - track each logo class: initial ACV, expansion curve, NRR by vintage.
- P&L (Income Statement) - revenue, COGS, gross profit, S&M, R&D, G&A, EBITDA.
- Cash Flow & Runway - monthly burn, ending cash, implied runway; size against raise proceeds.
- Balance Sheet - simplified; required for 3-statement close.
- KPI Dashboard - ARR, NRR, LTV/CAC (once data supplied), gross margin %, Rule of 40.
- Scenarios tab - toggle Base/Bull/Bear via a single input cell.
Frequently asked
Is the Daylight financial model free?+
Yes. The Daylight model is a free Excel (.xlsx) download with live formulas. Sign up with your email and the workbook is yours to keep, review, and edit.
What's included in the model?+
A 5-year monthly forecast with P&L, cash flow and runway, valuation (exit multiple plus a DCF cross-check), MOIC/IRR returns, and unit economics, with live formulas throughout.
How was this model built?+
It was built from Daylight's pitch deck and publicly available information, then structured to investment-banking standards as a fully editable Excel model.
Can I change the assumptions?+
Yes. You can change assumptions and the live formulas will recalculate in the downloadable Excel model.
Have more financial modelling questions? Contact us
Created by ex-finance professionals
Hey, I’m Alex and I created Finamodel.
Over my years in the finance industry I kept building the same models over and over again. Same structure, same assumptions, different logo. So I started building frameworks to turn them into clean, reusable templates.
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