# Oii AI Financial Model

AI-powered supply chain planning software that autonomously configures and optimises supply chain networks in real-time, layered on top of customers' existing planning systems.

- Canonical: https://finamodel.com/startups/oii-ai
- Excel download: https://finamodel.com/startup-models/oii-ai.xlsx
- Category: Logistics/Mobility
- Model type: SaaS ARR / Valuation
- Funding round: Seed
- Funding: $1.85M
- Founded: 2023
- Geography: UK-based (phone number +44 07767 382852, website orchestratedintelligence.com); pilot customers include US pharma majors (Gilead, Merck, GSK) and a UK food brand (Neom Organics London) - global ambition.
- Customer: B2B

## About the company

OII.ai provides autonomous supply-chain planning layered over customers’ existing systems. Its AI configures and optimises supply-chain networks in real time.

The revenue build should use enterprise contracts, planning volume, and SaaS ARR, separating implementation from recurring subscription revenue. Customer expansion should reflect wider usage of the planning platform.

Forecast implementation effort, churn, and cloud cost alongside contract growth. The model should show how planning volume and enterprise adoption translate into recurring revenue and delivery economics. It should preserve the distinction between the customer’s existing systems and OII.ai’s autonomous planning layer in real time, including network configuration and optimisation for each enterprise contract.

## 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: **Optii™** - patent-pending supply chain modelling platform that sits on top of existing ERP/planning systems (no rip-and-replace). Uses advanced simulation + AI/ML to auto-configure optimal supply chain network, run what-if scenarios, and provide real-time cost/service trade-off visibility.
- Next product in roadmap: **Autii MVP** - fully automated end-to-end supply chain planning system (Q1–Q2 2022 target).
- Key claimed outcomes from pilots: 30% total supply chain cost reduction; 25% inventory reduction; 75% reduction in planner activities; 25% service risk eliminated; 50% trade returns & discards reduction.
- Positioning: "GPS navigation for supply chain" - proactive, AI-cognitive, event-driven vs. reactive manual-configuration competitors.
- Differentiators vs. LLamasoft: operational (not project-based) usage model; planner-friendly (no PhD team needed); 1–3 month setup vs. 8–12 months; advanced simulation + AI vs. linear programming.
- Patent-pending; historical SC + sales data from 100s of thousands of SKUs across 9 global enterprises in 3 verticals used to train AI/ML models.

## Market

- **SC Modelling market**: $8.8B by 2025 at 20% CAGR.
- **Example sector - Pharma TAM** (Optii addressable): Setup fees $96M + Annual Recurring Revenue $118M. Based on 419 large/medium pharma companies × setup fees ($xxx–$xxxk per complexity) + 3–15 licenses per company @ $xxk p.a. per license.
- **Example sector - Retail TAM** (Optii addressable): Setup fees $1.8B + Annual Recurring Revenue $3.8B.
- Market context: 50% of companies embracing AI may double cash flow; cloud supply chain apps near-universal adoption cited; IIoT + digital twins accelerating.
- Note: exact global TAM across all sectors not stated; pharma and retail are illustrated examples only.

## Revenue model

Two-component model per customer:
1. **One-off setup / implementation fee**: $xxk–$xxxk depending on complexity.
2. **Annual recurring license fee**: $xxk per seat / per year; 3–15 seats per customer depending on business size.

Sales motion: direct enterprise sales via strategic-fit → capability-assessment → contracting pipeline. Pilot/POC first, then convert to commercial.
Partners: MarkLogic (technology), Trigyn Technologies (development & distribution).
Sectors targeted: pharma, food, retail (pilot evidence); M&A exit targets include Kinaxis, o9 Solutions, JDA, SAP, Oracle, anyLogistix, LLamasoft, Logility.

## Traction & metrics

- **PoC revenue to date**: "$XXXk PoC Revenue"
- **H1 2021 actual revenue**: "$XXXk"
- **Pilot/POC customers**: Gilead, Merck, GSK, Neom Organics London, Ramar Foods International.
- **Revenue targets** (redacted): H2 21/H1 22: "$X Million"; H2 22/H1 23: "$X Million"
- Product milestones achieved: Optii MVP (Q1 2020, tested w/ Pharma 1); MVP 2 (Q2 2020, E2E tested w/ Pharma 2 & Food 1); V1 (Q4 2020, POC w/ Pharma 3, 2 factories/global demand); V2 (Q3 2021, updated UI, carbon footprint modelling, what-if scenarios).

Note: all revenue figures are redacted ($XXXk / $X million) - exact numbers not available from deck.

## Competition / moat

- **Direct competitors**: LLamasoft (focus: retail, $1B+ companies, project-based, US-centric), Logility, anyLogistix, Infor, E2OPEN, SAP IBP, Oracle.
- **Competitive positioning**: Oii claims top-right quadrant (fast ROI + high savings) vs. slower/lower-ROI incumbents.
- **Moat claimed**: Patent-pending technology; AI trained on proprietary dataset (9 enterprises, 100s of thousands of SKUs, 3 verticals); no rip-and-replace required; operational (daily) vs. project-based usage.
- **M&A appeal**: positioned as acquisition target for Kinaxis, o9, JDA, SAP, Oracle, anyLogistix, LLamasoft, Logility.

## Team & funding ask / use of funds

**Team**:
- Bob Rogers, PhD (CEO) - Harvard PhD Physics; prior startup sold in 2020 for $XXX million (amount redacted).
- David Evans (COO) - MSc Computer Science, MSc Supply Chain Management.
- Lee Clewley, PhD (Advisor) - Imperial PhD Astrophysics; leader in SC modelling.
- Combined: 60+ years supply chain + AI expertise.

**Funding ask**:
- Seeking up to $X million seed round (exact amount redacted).
- Use of funds split three ways (individual allocations redacted as "$X.XM" each):
  1. Build production version of Optii (V2 UI, automated modelling engine, integration framework).
  2. Onboard operational team (support build, pilots, operations).
  3. Build sales & marketing capacity (pipeline, partnerships, marketing).
- Goal: become #1 supply chain optimisation software in 4–6 years.

---

## Recommended financial model

**Archetype + why**: Enterprise SaaS with upfront setup fee + annual recurring license (hybrid ARR model). The business has two distinct revenue streams - a one-off implementation fee (recognised at go-live) and recurring per-seat annual licenses. This is a classic land-and-expand SaaS model where pilots convert to commercial deployments and seat count grows with customer size. Model should track new logos, seat expansion, and churn separately.

**Forecast horizon & granularity**: 5 years (H2 2021 → FY 2026); quarterly for Years 1–2, annual for Years 3–5. Matches the deck's revenue target cadence and the 4–6 year market leadership goal.

**Key drivers & assumptions**:

*Revenue drivers:*
- New logos won per half-year (pilot → commercial conversion rate)
- Average setup fee per customer
- Average seats per customer at go-live
- Annual license fee per seat per year
- Seat expansion rate per existing customer per year
- Annual logo churn rate
- Revenue recognition: setup fee at go-live (one-time); license monthly ratable

*Cost drivers:*
- Headcount: R&D/engineering (largest bucket - building Optii V2 + Autii), sales (enterprise AEs + SEs), implementation/CS, G&A
- Cloud/infra cost per customer
- Sales & marketing spend
- Partner/distribution commissions (Trigyn)

*Scenario variables:*
- Pilot-to-commercial conversion rate (most sensitive)
- Average deal size (setup + seats)
- Time to close (enterprise sales cycles can be 6–18 months)

**Scenarios (Base / Bull / Bear - which variables flex)**:
- **Base**: 30–40% pilot conversion, mid-range deal size, 12-month avg sales cycle.
- **Bull**: 50%+ conversion, faster cycles (9 months), seat expansion at upper end, two sectors (pharma + retail) penetrated simultaneously.
- **Bear**: Slow conversion (20%), longer cycles (18 months), predominantly single-sector, higher churn.

**Required sheets / outputs**:
1. **Assumptions** - all drivers with / tags, switchable by scenario
2. **New Business Model** - logo adds, setup revenue, seat adds per cohort, ARR bridge
3. **P&L** - Revenue (setup + license), COGS, Gross Profit, OpEx (R&D, S&M, G&A), EBITDA
4. **Headcount Plan** - by function, by quarter
5. **Cash Flow** - operating + investing; runway analysis against seed round
6. **ARR Waterfall** - new, expansion, churn, net new ARR by period
7. **KPI Dashboard** - ARR, logo count, ACV, NRR, CAC, LTV:CAC, runway months
8. **Scenarios** - Base / Bull / Bear toggle

## Frequently asked questions

### Is the Oii AI financial model free?

Yes. The Oii 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.