Oxbotica Financial Model
Enterprise/Security Startup Financials (Free Excel Download)
Autonomy software platform provider enabling Level 4 self-driving across off-road, industrial, and on-road applications.
professionals from Deloitte
Used by professionals from
About this model
Oxbotica develops autonomy software for Level 4 self-driving applications across off-road, industrial, and on-road settings. Its Selenium and Caesium software is intended for fleet operators and OEM partners that need autonomous capability without building the full technology stack themselves.
The business combines recurring software licences with milestone-based engineering and integration work. Revenue is deployment-gated: customers typically require a project and technical integration before recurring licences begin, which makes timing and partner delivery more important than in pure SaaS.
The model schedules partnerships, engineering milestones, go-live dates, recurring licence fees, and professional services separately. It tracks deployment success, fleet scale, renewal, delivery cost, R&D, gross margin, and capital needs across industrial and automotive adoption scenarios.
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 Oxbotica
oxbotica.com
How to build a detailed financial model for Oxbotica
A complete walkthrough of the business, drivers, and assumptions behind the downloadable Oxbotica model - distilled from its pitch deck and publicly available information.
Product & value proposition
- Two core software products:
- Selenium - end-to-end autonomy platform (localisation, perception, mapping, tracking, planning & control, simulation). Modular; individual modules can be sold standalone.
- Caesium - cloud-based fleet data and vehicle management suite (monitoring, data analytics, scheduling, map management).
- Technology USPs:
- Sensor-agnostic, vehicle-agnostic, place-agnostic ("Universal Autonomy").
- Universal Localisation: 6DOF, cm-precision, works without GPS, cloud-based map management.
- Universal Perception: supports vision, radar, laser; ML + optimisation dual approach; ultra-low power.
- Open API, modular architecture designed for safety; edge and cloud components.
- Tagline: "Universal Autonomy" - one platform across all vehicle types and environments.
Market
- No TAM/SAM/SOM figures or market-size numbers are shown in this deck.
- Addressed verticals identified qualitatively: Mining, Airports, Ports, Shuttles (people carriers), Goods Delivery - with Mining, Shuttles, and Goods Delivery as current go-to-market focus.
- Market selection scored across: Universal Core Applicability, Application Engineering effort, Safety & Validation effort, Market Immediacy, Market Value - presented as relative-magnitude chart (0–10 scale, qualitative).
Revenue model
- Revenue model stated as recurring software licence fees.
- Products can be sold as a full platform or as standalone modules for earlier revenue.
- Channels: commercial partnerships with vehicle OEMs and integrators (ZF, Ocado, Addison Lee, Wenco), consortium projects (DRIVEN), government-backed pilots (GATEway, Heathrow, Gatwick).
- No pricing, ACV, or per-vehicle/per-km fee structure disclosed in deck.
Traction & metrics
- No revenue figures, customer counts, or ARR disclosed.
- Milestone traction (qualitative):
- 2015: Products launched (Selenium, Caesium).
- 2016: First public self-driving test in UK; AXA XL collaboration signed.
- 2017: GATEway shuttle deployment (Greenwich); Ocado delivery partnership; DRIVEN consortium.
- 2018: Driverless trials at Gatwick and Heathrow; OEM integration trials in Asia; Addison Lee partnership; first mine trial.
- 2019: Fleet deployed in London urban environment; ZF collaboration.
- 2020: Commercial L4 deployment in mine (first commercial deployment noted); ZF hardware integration and on-road deployment; Cisco OpenRoaming partnership; Wenco MoU; first on-road MaaS trials across large UK cities.
- "Key commercialisation partnerships established" - no contract values given.
Competition / moat
- Competitive differentiation stated qualitatively:
- Moat 1: Sensor, vehicle, and place agnosticism - enables more markets than rivals.
- Moat 2: Universal Localisation "surpasses all other solutions in reliability and precision" (self-stated).
- Moat 3: Low-power edge compute footprint lowers cost of commercialisation.
- Moat 4: Platform modularity - early revenue from components while full-stack deals mature.
- Moat 5: Oxford University research pedigree (SLAM pioneers Paul Newman & Ingmar Posner).
- Moat 6: Established partnerships with ZF, Ocado, AXA XL, Cisco, Wenco, Addison Lee.
- No named competitors shown; no competitive matrix in deck.
Team & funding ask / use of funds
- Team:
- Ozgur Tohumcu, CEO (former CEO Tantalum; Ericsson/Sapient/CGI).
- Paul Newman, Founder & CTO (BP Professor, Oxford; MIT; SLAM pioneer).
- Marta Ostroumoff, Finance Director (former Prodrive Head of Finance; FCA).
- Richard Jinks, VP Commercial (former AXA XL Global Autonomy Programme Lead).
- Ben Upcroft, VP Technology (former Associate Professor Robotics, QUT).
- Graeme Smith, SVP External Affairs (original CEO 2014–2019; Ford Director; PhD Robotics).
- Tony Lowe, Interim COO (former Chief Delivery Officer, Tantalum; JLR Connected Car co-founder).
Recommended financial model
- Archetype + why: B2B Autonomy Software - ARR / recurring-licence model with milestone-based professional services. Oxbotica sells recurring software licences (Selenium + Caesium) to fleet operators and OEM partners, with implementation engineering that precedes licence revenue. The right model is a SaaS/licence ARR build layered with a project-based professional-services line, rather than a pure SaaS or pure 3-statement model. Revenue is deployment-gated: each customer partnership requires integration work before recurring licence fees commence.
- Forecast horizon & granularity: 5 years (2021–2025), monthly for Year 1 (cash management), quarterly thereafter. Given early commercial stage with lumpy project timelines, monthly granularity matters in near term.
- Key drivers & assumptions:
| Driver | Value / Range | Source |
|---|---|---|
| Vertical segments | Mining, Shuttles, Goods Delivery (near-term); Airports, Ports (later) | - |
| Licence model | Per-vehicle/per-fleet annual recurring licence | industry norm; deck says "recurring software revenue" but no per-unit pricing given |
| Annual licence fee per vehicle | £X,000–£XX,000 (placeholder) | comparable AV software deals (e.g. Mobileye, Waymo licensing discussions) suggest £10k–£50k/vehicle/year; to be confirmed |
| Vehicles under licence - Year 1 | Small (5–20 vehicles, mining + shuttle pilots) | based on 2020 first commercial mine deployment being a single site |
| Fleet growth rate per deployment | 2–3x per year per vertical as pilots convert to commercial | typical hardware ramp for autonomous mining/logistics |
| New verticals added | 1 new vertical per year post-2022 | rationale: platform architecture supports it; go-to-market bandwidth limits faster expansion |
| Professional services / integration revenue | 15–25% of total revenue in early years, declining to <10% by Year 5 | consistent with enterprise software transitions |
| Gross margin - software licences | 70–80% | deep tech SaaS; high R&D costs but low COGS per additional licence |
| Gross margin - professional services | 20–35% | engineering-intensive; comparable to automotive software integrators |
| R&D spend | 50–60% of revenue in Years 1–2, declining to 30–40% by Year 5 | pre-profitability deep tech norm; Oxbotica is still productising |
| Sales & marketing | 10–15% of revenue | partnership-led go-to-market (low direct sales); government/consortium channels reduce CAC |
| G&A | 15–20% of revenue | - |
| Headcount growth | Engineering-heavy; ~60–70% of hires in R&D | - |
| Cash burn / runway | To be sized against raise; deck implies pre-profitability Series B/C stage | - |
- Scenarios (Base / Bull / Bear - which variables flex):
- Base: Mining + Shuttle + Goods Delivery ramp as modelled; ZF and Wenco partnerships yield first fleet licences by 2022; modest ASP.
- Bull: Faster fleet ramp (mining scales faster; ZF OEM volume accelerates); additional verticals (Airports, Ports) enter 2023; higher ASP driven by exclusivity with OEM partners.
- Bear: Partnership timelines slip (regulatory delays in UK AV legislation); commercial deployments remain single-site pilots; professional services revenue dominant and margin-dilutive.
- Key flex variables: vehicles under licence per partner, ASP per vehicle, time-to-commercial per vertical, professional-services revenue mix, and R&D headcount cost.
- Required sheets / outputs:
- Assumptions - all drivers in one input block; colour-coded vs.
- Revenue build - by vertical (Mining, Shuttles, Goods Delivery, Other); split licence vs. professional services; vehicles × ASP × utilisation.
- P&L (Income Statement) - revenue, gross profit, R&D, S&M, G&A, EBITDA, net loss.
- Headcount plan - by department (Engineering/R&D, Commercial, G&A); linked to opex.
- Cash flow & runway - operating cash burn + raise proceeds; months of runway.
- ARR bridge - opening ARR, new ARR, expansion ARR, churn, closing ARR (annual).
- Scenario toggle - Base / Bull / Bear switching assumptions block.
- KPI dashboard - vehicles under licence, ARR, gross margin %, burn rate, runway.
Frequently asked
Is the Oxbotica financial model free?+
Yes. The Oxbotica 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 Oxbotica'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.
Every model here is one I’d actually use for a client, and I personally vet each one before it goes up.
I’m not an expert in every industry, but I’ve built enough models to know what belongs in one. And when something is completely foreign to me, I reach out to my network for experts to work on our models with us.
Having a template library on hand cuts a first build from hours to minutes.
Need help finding your model? You’ll find me in the Finamodel app!
Other Enterprise/Security Startup Financial Models
Browse another startup in the same category.
AgBiome
AgBiome is a microbial-platform agtech company that discovers, develops, and commercialises biological crop protection products (and licences the platform across adjacent markets).
Alation
Enterprise data intelligence platform - data catalog, governance, and metadata management for large organisations.
Archer SPAC
Archera
Cloud resource automation platform that continuously optimizes AWS commitment purchases, de-risks overcommitment, and automates FinOps workflows.
Ardoq
Cloud-native Enterprise Architecture (EA) SaaS platform that helps large enterprises navigate digital transformation through automated data collection, graph-based architecture modelling, and change impact analysis.
Ascend
Ascend.io is an enterprise big data automation platform ("Enterprise Intelligence Platform") that abstracts away the complexity of big data engineering so non-experts can build and run data pipelines.
Athennian
Cloud-based legal entity management system (EMS) uniting entity data with workflow and document automation.
Auditboard
Cloud-based integrated risk management platform connecting audit, risk, compliance, and ESG teams across the enterprise.
