Help Lightning Financial Model
AI/ML Startup Financials (Free Excel Download)
JIFFY.ai (by Paanini Inc.) is an AI/ML-driven low-code/no-code enterprise automation platform combining RPA, NLP, document processing, and workflow in a multi-tenant cloud architecture.
professionals from Deloitte
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About this model
Help Lightning provides visual remote-assistance software for service teams. Through mobile or web collaboration, a remote expert can annotate a field technician's live view and guide maintenance or repair work without always travelling to the site.
The enterprise platform supports industrial and service workflows where a technician needs immediate specialist help. Its product combines video collaboration with augmented-reality-style visual guidance, helping organisations reduce travel, shorten resolution time, and preserve expert knowledge across distributed teams.
The model builds recurring ARR from enterprise accounts, service locations, and technician seats, then captures expansion and churn by cohort. It tests implementation and support cost, customer-success capacity, sales productivity, gross margin, R&D hiring, cash burn, and runway against adoption and avoided-travel outcomes.
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 Help Lightning
helplightning.com
How to build a detailed financial model for Help Lightning
A complete walkthrough of the business, drivers, and assumptions behind the downloadable Help Lightning model - distilled from its pitch deck and publicly available information.
Product & value proposition
Three product lines under the JIFFY.ai umbrella:
- JIFFY.ai AUTOMATE - enterprise BPA platform; RPA + ML + workflows + analytics; low-code app builder; multi-tenant SaaS.
- JIFFY.ai ASSURE - intelligent continuous test automation.
- JIFFY.ai INNOVATE - AI-driven software development from natural language / spoken specs.
Platform stack layers: Designer Tools (Bots/Apps Studio, Workflow Studio, KPI Analytics, AI/ML Workbench), Cognitive Layer (IDP, OCR, NLU/NLP, ML Algorithms), Execution Layer (Bot Orchestration, APIs, Web/Desktop/Green Screen).
Differentiation: app-based automation concept ("HyperApps"); no-code natural-language app generation; combined RPA + cognitive AI in a single platform.
Revenue model
Not explicitly stated in deck. Inferred from product type and partner list:
- Subscription/ACV SaaS licensing: annual contracts per platform module (AUTOMATE, ASSURE, INNOVATE). Common pricing in enterprise RPA = per-bot or per-user seat. Rationale: multi-tenant cloud architecture and enterprise client base are consistent with annual license + professional services.
- Services / implementation revenue: likely a meaningful share given SI partners (Accenture, KPMG, Deloitte, Cognizant, Wipro, TCS, Capgemini). Rationale: complex enterprise automation deployments typically require onboarding/customization services.
- Channel / partner revenue share or referral from SI alliances. Rationale: named as "Select Partners" on slide 5.
Traction & metrics
All from slide 5:
- 20 co-founders
- 150 team size
- 6 Fortune/Global 500 clients
- 2 patents pending
- Offices: Palo Alto, Boston, Bangalore, Trivandrum
Client verticals:
- Airline/Travel: largest low-cost airline in the US
- Manufacturing: one of the largest vehicle manufacturers in Europe
- Banking/FS: one of the largest card payment processors in APAC
- Insurance: one of the largest life insurance companies in the Middle East
- Retail: 3 Fortune 500 retailers in US
- Telecom: 4 global telecom providers
Awards/recognition:
- Top 10 Disruptor - RPA & Cognitive Data Processing (2019)
- IDC Game Changer for Financial Services (2019)
- Gartner Honorable Mention, Magic Quadrant for RPA (2019)
No revenue figures, ARR, growth rates, NRR, or customer count beyond above are shown in the deck.
Unit economics
Case-study efficiency outcomes shown (client-side, not vendor economics):
- 90% resource reduction at peak (Journal Vouchers)
- 100% automation of JV processing
- 85% reduction in overdue invoices
- 80% reduction in invoice processing time
- 75% straight-through processed invoices
Competition / moat
Not explicitly addressed. Implied differentiation:
- First "app-based" approach to automation (claimed)
- Combines RPA + ML/NLP + test automation + software development in one platform
- Low-code/no-code entry; natural language app generation
- Gartner MQ presence (2019, honorable mention) confirms competitive positioning vs. UiPath, Blue Prism, Automation Anywhere
Team & funding ask / use of funds
Team:
- Babu Sivadasan - Chairman & CEO
- Hari Menon - Group President, Product & Strategy
- Kris Subramanian - President & COO
- Payeli Ghosh - Chief People, Marketing & Operations Officer
- Regi Roy - Chief Customer Success Officer
- Sales VPs covering Financial Services (David Baker), Europe (Zora Arnautovic), APAC (Sangeetha Phalgunan)
- Advisors: Robert Ward, Dino Di Palma
- Expertise: NLP, AI/ML, Enterprise Software, Banking & FS, IT Outsourcing, IP
Recommended financial model
- Archetype + why: Enterprise SaaS ARR model with a professional services revenue line. JIFFY.ai sells multi-module annual contracts to large enterprises via direct sales and SI partners - classic high-ACV, low-volume enterprise SaaS. A professional services / implementation line is almost certain given the partner ecosystem and complexity of deployments.
- Forecast horizon & granularity: 5 years (Year 1–5), annual granularity. Monthly detail for Year 1 if run rate / cash burn is needed.
- Key drivers & assumptions:
| Driver | Value |
|---|---|
| Starting ARR | Unknown |
| New logos per year | Unknown |
| Average contract value (ACV) | Unknown |
| Net Revenue Retention (NRR) | Unknown |
| Gross margin (software) | Unknown |
| Services mix | Unknown |
| Sales cycle | Unknown |
| Headcount (150 staff) | 150 |
| Offices | Palo Alto, Boston, Bangalore, Trivandrum |
| Partner channel contribution | Unknown |
- Scenarios (Base / Bull / Bear - which variables flex):
- Bear: Slow new logo adds (2–4/year), low ACV, high churn, services-heavy mix → ARR growth <30% YoY
- Base: Moderate logo adds, ACV at midpoint, NRR ~115%, services ~25% → ARR growth 50–70% YoY
- Bull: Accelerated SI channel pull-through, multi-module expansion, platform wins in APAC/EU, NRR >120% → ARR growth >100% YoY
- Required sheets / outputs:
- Assumptions - all drivers with Base/Bull/Bear toggles
- ARR Bridge - opening ARR, new bookings, expansion, churn, closing ARR by year
- Revenue P&L - SaaS license revenue, professional services revenue, total revenue
- Gross Profit - blended gross margin split by line
- OpEx - R&D, S&M (direct + channel), G&A, headcount build
- EBITDA / Operating Loss - path to breakeven
- Cash Flow / Runway - burn rate, cash position (if raise amount known)
- KPI Dashboard - ARR, logo count, ACV, NRR, CAC payback, LTV/CAC
Frequently asked
Is the Help Lightning financial model free?+
Yes. The Help Lightning 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 Help Lightning'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
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