# Time by Ping Financial Model

AI-powered time automation software that automatically captures, contextualises, and releases billable time entries for legal timekeepers.

- Canonical: https://finamodel.com/startups/time-by-ping
- Excel download: https://finamodel.com/startup-models/time-by-ping.xlsx
- Category: Enterprise/Security
- Model type: SaaS ARR / Valuation
- Funding round: Series B
- Funding: $36.5M
- Founded: 2022
- Geography: USA (implied by legal market sizing and firm references) [DECK].
- Customer: B2B

## About the company

Time by Ping uses AI to automatically capture, contextualise, and release billable time entries for legal timekeepers. It addresses lost billable time by fitting time capture into lawyers' existing work rather than requiring delayed manual entry.

The company sells seat-based subscriptions to law firms and was raising a Series B in 2021. Legal is the initial vertical, with a planned expansion into accounting and consulting, so timekeepers and firm-level adoption are the practical revenue units.

The model tracks firms, new timekeepers, pricing, expansion, and churn by vertical. AI processing, integrations, and support form delivery costs, while sales capacity, gross margin, product investment, hiring, and operating expenses determine ARR growth and runway.

## 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: "Time Automation™" - desktop/browser software that passively captures all digital activity (emails, documents, meetings, phone calls, browser research) across Outlook/Exchange, Microsoft Suite, Adobe/KOFAX PDF, Cisco/Jabber/Zoom/Teams, IE/Edge/Chrome.
- ML pipeline: Named Entity Recognition + NLP + Machine Learning converts raw activity into structured time entries with Client/Matter, Narrative, and Billing Codes auto-populated.
- UX: Timeline and Timesheet views; time entries released daily by timekeepers, not reconstructed at month-end.
- Three-phase vision: Phase 1 = Time Automation (current); Phase 2 = Time → Outcomes (pricing analytics using aggregated time data); Phase 3 = Outcomes → Time (extend to all digital workers).

## Market

- Industry problem: Professional services industry loses 2,000 years of time / $7.4B in productivity daily from manual time tracking.
- Legal industry specifically leaves $140B on the table annually due to manual timekeeping.
  - 20% of total work time is never billed
  - 18% of total work time is client-rejected
  - 5% of total work time is spent manually tracking
- Addressable ARR market (legal, by segment):
  - Enterprise Legal: $1B ARR
  - Corporate Legal: $0.5B ARR
  - SMB Legal: $2B ARR
  - Total Legal ARR Opportunity: $3.5B
- Expansion ARR market (legal + adjacent):
  - Accounting: $2.5B ARR
  - Legal: $3.5B ARR
  - Consulting: $4B ARR
  - Total ARR Opportunity: $10B
- Workforce sizing for Phase 3 expansion:
  - Law: 1.1M workers
  - Accounting: 1M workers
  - Consulting: 1.6M workers
  - Tech: 6M workers
  - 1099s: 16M workers
  - Government: 20M workers
  - Digital Workers worldwide: 1B

## Revenue model

- Model type: SaaS subscription, billed per timekeeper (seat-based) - implied by the $90K profit-per-timekeeper ROI framing and "ARR" language used throughout.
- Channels: Enterprise top-down (current flagship); Series B use of proceeds includes adding bottoms-up / product-led growth distribution.
- Verticals: Legal (current); Accounting and Consulting (expansion).
- Lighthouse reference customers: unnamed "premier law firm" (slide 11) and unnamed "major accounting firm" (slide 16).

## Traction & metrics

- ROI case study - premier law firm:
  - $90K direct bottom-line profit per Timekeeper
  - Only 2 timekeepers using TBP needed to recoup the firm's cost
  - 1 dedicated resource hired by firm to maximize value
- Product outcomes:
  - 1–2 hours saved per timekeeper per week
  - 7.5% more billable credit on average per timekeeper
  - 7.5% more revenue on average for firms
  - 70% of users release time daily (engagement metric)
  - 35% more time entries per user

## Unit economics

- LTV proxy: $90K bottom-line profit per seat per year for the customer (implies strong willingness to pay and high retention).

## Competition / moat

- Incumbent: Manual timekeeping (status quo). No direct named competitors in the deck.
- Moat claims:
  - Proprietary ML trained on legal billing data (NER, NLP, billing codes).
  - Network/data flywheel: aggregated time data across industry creates a pricing analytics layer competitors cannot replicate (Time Data Feedback Loop).
  - "New market category" positioning - Time Automation™.
  - Deep integrations: Outlook/Exchange, MS Suite, Adobe/KOFAX, Cisco/Jabber/Zoom/Teams, major browsers.

## Team & funding ask / use of funds

- Raise: $30M Series B.
- Use of funds:
  1. Grow ARR in Enterprise and SMB Legal in 2022.
  2. Expand Time Automation into Enterprise Accounting and Consulting.
- Team (13 named):
  - Ryan, CEO - Lawyer @ Manatt
  - Patrick, CTO - SVP @ Symantec
  - Alison, CS - Senior CS Mgr @ Scoop
  - Tara, Sales - VP @ Afinety
  - Kourosh, COO - Founder @ YPOSF; VP @ Bailard
  - Niket, Product - Founder @ Punchd (acq. Google); CoS @ Flipkart
  - Jon, Strategy - First GTM @ Everlaw
  - Mallory, Ops - Founder @ Verto
  - Michael, Design - First Designer @ Nest
  - Sarah, Eng - Engineering Manager @ Xero
  - Chris, Legal - Lawyer @ Paul Hastings
  - Sydney, Marketing - First Marketer @ Proscia
  - Ravi, Engineering - Engineering Leader @ Point Card
- Investor type sought: Mission-oriented, vision-aligned, PLG experience, cross-vertical experience, generational company builders.

## Recommended financial model

- **Archetype + why:** SaaS ARR model (seat/timekeeper-based). Revenue is explicitly framed as ARR, growth is seat-driven, and the company segments market opportunity by ARR vertical. A 3-statement wrapper is secondary but useful for burn/runway given the $30M raise context.

- **Forecast horizon & granularity:** 5 years (2022–2026); monthly for Year 1–2 (to show PLG ramp and burn), annual thereafter.

- **Key drivers & assumptions:**

| Driver | Value |
| -- | -- |
| Starting ARR (end of 2021) | Unknown - use placeholder $Xm |
| Enterprise Legal seats (Y1 target) | Model-driven from legal firm count |
| Average Contract Value (ACV) per seat | $X,000/yr (placeholder) |
| Net Revenue Retention (NRR) | 110–120% |
| Gross margin | 75–80% |
| Logo churn | 5–10% annually |
| New logo adds per quarter (Enterprise Legal) | ramp from existing base |
| PLG seat adds (SMB Legal, Y2+) | bottoms-up motion starts post-Series B |
| New vertical entry (Accounting) | Year 2 |
| New vertical entry (Consulting) | Year 3 based on roadmap sequencing |
| Legal TAM (ARR) | $3.5B |
| Total 3-vertical TAM (ARR) | $10B |
| Headcount growth (S&M, R&D, G&A) | sized to $30M raise and 5-year plan |
| Burn / runway | from headcount + infra opex vs. ARR |

- **Scenarios (Base / Bull / Bear - which variables flex):**
  - Bear: slower Enterprise Legal seat growth, no SMB PLG take-off, Accounting entry delayed to Y3; NRR 105%.
  - Base: Enterprise Legal ramp per stated plan, SMB PLG begins Y2, Accounting Y2, Consulting Y3; NRR 115%.
  - Bull: faster PLG adoption, Accounting lighthouse converts to enterprise rollout early, NRR 125%+, expansion into Tech workers begins.

- **Required sheets / outputs:**
  1. Assumptions - all drivers, scenario toggles (Base/Bull/Bear via CHOOSE).
  2. ARR Bridge - starting ARR, new logo ARR, expansion ARR, churn ARR, ending ARR; monthly Y1–2, annual Y3–5.
  3. Seat / Customer Count - by vertical (Enterprise Legal, SMB Legal, Corporate Legal, Accounting, Consulting).
  4. Revenue & Gross Profit - ARR, recognised revenue, COGS, gross margin %.
  5. Opex - S&M (incl. PLG CAC), R&D, G&A; headcount by function.
  6. P&L - EBITDA / operating loss, path to profitability.
  7. Cash & Runway - burn rate, months of runway from $30M raise.
  8. Unit Economics - ACV, CAC (blended enterprise + PLG), LTV, LTV/CAC, payback period.
  9. Market Penetration - ARR as % of $3.5B legal TAM and $10B total TAM.
  10. Dashboard - KPI cards: ARR, seats, NRR, gross margin, burn, runway.

## Frequently asked questions

### Is the Time by Ping financial model free?

Yes. The Time by Ping 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.