# JIFFY.ai Financial Model AI-driven low-code/no-code enterprise automation platform combining RPA, ML, NLP, document processing, and workflow into "HyperApps" - Canonical: https://finamodel.com/startups/jiffyai - Excel download: https://finamodel.com/startup-models/jiffyai.xlsx - Category: Dev Tools - Model type: SaaS ARR / Valuation - Funding round: Series A - Funding: $18M - Founded: 2020 - Geography: Global - HQ Palo Alto; offices in Boston, Bangalore, Trivandrum; clients in US, Europe, APAC, Middle East [DECK slide 5] - Customer: B2B ## About the company JIFFY.ai is an enterprise automation platform combining RPA, machine learning, NLP, document processing, workflow, test automation, and development automation. Its modular products are designed for large organizations that want to build and deploy automated business processes and HyperApps. The company had six Fortune or Global 500 clients, a 150-person team, and a go-to-market route through major systems integrators. Revenue is expected to come from enterprise platform licenses with professional-services and partner implementation attachments. The model is an enterprise SaaS ARR forecast with services. New logos, module adoption, contract value, expansion, renewal, and SI-sourced pipeline build recurring revenue; implementation and support form a secondary line. Partner economics, sales cycles, delivery capacity, and retention determine profitability. ## 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 Three product lines under the JIFFY.ai brand: - **JIFFY.ai AUTOMATE** - Enterprise BPA platform; RPA + ML + Workflow + Analytics; low-code app store model; multi-tenant cloud - **JIFFY.ai ASSURE** - End-to-end intelligent continuous test automation for agile enterprises - **JIFFY.ai INNOVATE** - Software development automation from natural-language/voice specifications; deploy to production in real time Differentiator: "HyperApps" concept - combines RPA, ML/NLP, workflow, and document intelligence in reusable vertical apps; low-code/no-code for business users; cloud-native multi-tenant architecture deployable on public/private cloud or on-premise. Platform stack layers: Designer Tools (Bots & Apps Studio, Workflow & Forms Studio, Process KPI Analytics, AI/ML Workbench); Cognitive Layer (Intelligent Doc Processing, OCR/Image Recognition, NLU/NLP, Pre-packed ML library); Execution Layer (Bot Orchestration, Application APIs, Web UI/Green Screen/Desktop, Alerts). ## Revenue model Not explicitly stated in deck. Inferred from platform description: - Platform subscription / SaaS license: enterprise contracts for AUTOMATE, ASSURE, INNOVATE modules; likely annual recurring license + professional services attach. Rationale: standard enterprise RPA/IPA go-to-market. - Partner/channel revenue: SI partnerships (Accenture, KPMG, Deloitte, Cognizant, Wipro, Tech Mahindra, TCS, Capgemini) likely drive implementation revenues and referral/resell arrangements. - Usage/consumption component possible for bot orchestration (bot hours/task volume) - common in RPA pricing - but not stated in deck. ## Traction & metrics All from slides 5 and 4: - 20 co-founders - 150 team size - 6 Fortune/Global 500 clients - 2 patents pending - Offices in Palo Alto, Boston, Bangalore, Trivandrum - Vertical client examples: largest low-cost airline in US; one of largest vehicle manufacturers in Europe; one of largest card payment processors in APAC; one of largest life insurance companies in Middle East; 3 Fortune 500 retailers in US; engagements with 4 global telecom providers No ARR, revenue, growth rate, churn, or NRR figures disclosed. ## Unit economics Customer outcome metrics shown (case study context, not company-level financials): - 90% less resources at peak (Journal Vouchers) - 85% reduction in overdue invoices - 100% automation of recon / MDM requests - 80% of receipts auto-matched; 80% reduction in GL clearing effort - 1,000+ invoice formats auto-processed - 95% exceptions handled via Jiffy.ai - 98% of customers auto-copied (Interface Development) - 85% of reimbursements read, audited, and paid (Expense Mgmt) - 75% straight-through processed invoices; 80% reduction in invoice processing time - 90% reduction in manual processing effort (Compliance/Internal Audit) - 100% rule application across full dataset ## Competition / moat Not explicitly addressed in deck. Implied moat: - "First to design an app-based approach to automation" - HyperApps concept bundling RPA + ML + NLP + workflow (vs. point solutions) - 2 patents pending - SI ecosystem (Big 4 + top SIs as partners) creates distribution and stickiness - Gartner MQ Honorable Mention (RPA 2019) and IDC Game Changer (FS 2019) No direct competitor comparison slide in deck. ## Team & funding ask / use of funds Team: - Babu Sivadasan - Chairman & CEO - Kris Subramanian - President & COO - Hari Menon - Group President, Product & Strategy - Payeli Ghosh - Chief People, Marketing & Operations Officer - Regi Roy - Chief Customer Success Officer - Regional VP Sales: David Baker (Financial Services), Zora Arnautovic (Europe), Sangeetha Phalgunan (APAC) - Advisors: Robert Ward, Dino Di Palma Stated expertise: NLP, AI/ML, Enterprise Software, Banking & Financial Services, IT Outsourcing, IP. --- ## Recommended financial model - **Archetype + why:** Enterprise SaaS ARR model with a services attach layer. Jiffy.ai sells multi-module platform licenses to large enterprises through SI partners - the right archetype is an ARR/TCV build-up driven by new logo wins, expansion ARR, and a professional services revenue line. Given the SI-heavy GTM, a partner-sourced vs. direct-sourced split is also warranted. - **Forecast horizon & granularity:** 3 years (monthly Year 1, quarterly Years 2–3). Monthly is needed in Year 1 to model sales cycle timing and services ramp per client. - **Key drivers & assumptions:** *Revenue* - Number of new enterprise logos per year - Average ACV per logo - Modules per client (AUTOMATE / ASSURE / INNOVATE) - Expansion ARR rate (NRR > 100%) - Gross churn - Professional services attach rate - Partner/SI sourced % of pipeline *Cost structure* - R&D headcount & salaries - G&A, Sales, CS headcount - COGS: cloud hosting + customer success - Target gross margin *Headcount* - Current: 150 - Growth: 30–40% YoY scaling in Sales/CS/Engineering as ARR ramps - **Scenarios (Base / Bull / Bear - which variables flex):** - **Base:** 5 new logos/yr Y1, $400K ACV, 115% NRR, 70% gross margin - **Bull:** 8 new logos/yr Y1, $550K ACV, 125% NRR, fast SI-channel ramp - **Bear:** 3 new logos/yr Y1, $300K ACV, 105% NRR, elongated sales cycles, higher services mix - **Required sheets / outputs:** 1. Assumptions - all drivers centralized 2. Revenue Build - ARR waterfall (beginning ARR + new + expansion − churn = ending ARR), MRR/ARR by module 3. Headcount Plan - by department, cost per head 4. P&L - Revenue (SaaS + services), COGS, Gross Profit, OpEx (S&M, R&D, G&A), EBITDA 5. Cash Flow - operating CF, capex (minimal), ending cash; burn rate 6. KPI Dashboard - ARR, logo count, NRR, CAC Payback, LTV/CAC, headcount 7. Scenarios - toggle (Base / Bull / Bear) ## Frequently asked questions ### Is the JIFFY.ai financial model free? Yes. The JIFFY.ai 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.