nTopology Financial Model
Hardware/Deep-tech Startup Financials (Free Excel Download)
Next-generation engineering design software (CAD/CAE) that enables advanced manufacturing workflows - latticing, field-driven design, topology optimization - impossible in legacy tools.
professionals from Deloitte
Used by professionals from
About this model
nTopology provides engineering design software for advanced manufacturing, latticing, and topology optimisation. It enables workflows that legacy CAD and CAE tools cannot easily deliver, targeting engineers who need computational design tools for complex parts and production methods.
Its commercial model is enterprise software sold into technical teams. Value grows as customers deploy the platform across engineers, programmes, and manufacturing workflows, but adoption can require specialised implementation and engineering support before the product becomes embedded in design processes.
Model enterprise customers, seats, contract value, implementation, usage expansion, renewals, and churn. Include engineering support, product development, cloud or licensing delivery, sales, and customer-success costs. New-logo wins, seats per customer, deployment speed, expansion, pricing, support intensity, and net retention should drive 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 nTopology
ntopology.com
How to build a detailed financial model for nTopology
A complete walkthrough of the business, drivers, and assumptions behind the downloadable nTopology model - distilled from its pitch deck and publicly available information.
Product & value proposition
- nTop (nTopology) is a computational geometry / parametric design software for advanced manufacturing (additive manufacturing, CNC, etc.).
- Key differentiator: "remixable workflows" - power users (Authors, ~11% of MAUs) build automated design workflows that non-expert engineers (Users, ~89% of MAUs) can run. This drives exponential seat expansion inside accounts.
- Outperforms incumbents (CATIA, Siemens NX, SolidWorks, Dassault) on speed and capability for complex geometries:
- vs. Dassault on helicopter parts: 48% weight reduction vs. 10%; 30 min design vs. 6 hrs.
- vs. Siemens NX on stealth wings: 60 min optimization vs. impossible; 30 min design vs. impossible.
- vs. CATIA on Ford auto structure node: optimization 1 hr vs. 3 hrs; design 4 min vs. 1 week.
- vs. legacy tools at Stryker (medical): enables 2,000+ engineers to design parts previously only 4 could; 2 min vs. 8 hrs design time.
- Positioned as a non-disruptive add-on: nTop slots into the Part Design phase of existing CAD workflows (SolidWorks, NX, etc.) without requiring full workflow replacement.
Market
- TAM framing: engineering software industry dominated by 41-year-old average-age incumbents:
- CAD (Design): $9B yearly spend
- CAE (Simulation): $8B yearly spend
- CAM (Manufacturing): $5B yearly spend
- Combined: ~$22B annual engineering software spend
- Incumbent market cap: $100B+ (Autodesk, Dassault, PTC, ANSYS, Siemens)
- Per-account total engineering software spend ceiling cited: $200M - appears to reference a single large enterprise account's full software budget.
- SAM / SOM: Not explicitly stated. No SOM figure given.
Revenue model
- Seat-based SaaS with land-and-expand tiering:
- Land (<90 days): ACV $15K–$40K, 2–6 users
- Expand (6–12 months): ACV $100K–$500K, 20–100 users
- Enterprise (>12 months): ACV $1M+, 125+ users
- 2019 blended ACV: $35.5K - consistent with early land-phase deals dominating.
- 2020 ACV (as of Q1 2020): $25K - lower than 2019; likely reflects a shift toward more land deals or pricing strategy change; no explanation given.
- Pipeline by type: 58% Enterprise, 43% Land (by pipeline value).
- Pipeline by industry: Aerospace & Defense largest, then Medical, Automotive, Consumer Goods, Manufacturing/Service Bureau, Research/EDU, Heavy Industry. Pipeline values reach ~$3M for top verticals visible on chart axis.
- Sales channel: Direct enterprise sales (CRO Steve Costello with PLM/CAD enterprise background). No mention of channel partners or self-serve.
Traction & metrics
- ARR: >$2M as of ~Q1 2020
- ARR target: $5M by end of 2020
- nTop product launched: ~Q2 2019
- User growth: >40% monthly user growth in 2020
- Users tripled since beginning of 2020; chart (slide 19) shows growth from ~0 in May 2019 to ~1,200–1,300+ by March 2020 (exact latest figure redacted)
- Account growth chart (slide 12) shows actual user count reaching ~160–170 users at ~21 months, trending projected to ~650–800 by 33 months - these appear to be aggregate nTop users across accounts, not individual account counts
- Per-account user expansion pattern: accounts that land at 2–6 users reach 20–100+ users within 6–12 months across multiple named enterprise accounts
- User mix: 89% design-engineer users, 11% authors (workflow creators)
- Engagement / retention metrics: all specific numbers redacted in deck (slides 20):
- Avg. time in nTop per session: redacted
- % of All MAUs who are DAUs: redacted
- % of Author MAUs who are DAUs: redacted
- 8-week product retention (including trials): redacted
- Q1 2020: described as "best quarter yet"; specific figures redacted
- Customer verticals in production: Aerospace & Defense (helicopter parts, stealth wings), Automotive (Ford structural node), Medical (Stryker, 500K parts/year), COVID-19 swabs
Unit economics
- Land-to-expand signal: deck claims accounts grow "exponentially" and multiple enterprise accounts show the same exponential user growth curve within 4 quarters of signing.
Competition / moat
- Named competitors: CATIA (Dassault Systèmes), Siemens NX, SolidWorks, Autodesk, PTC, ANSYS.
- Competitive positioning: incumbents average 41 years old; all were built before additive manufacturing and field-driven design existed.
- Moat claims:
- Workflow remixability: only engineering software with "robust remixable workflows" - Authors encode expertise into reusable apps that non-experts can run, creating a network effect within accounts.
- Computational geometry IP: founder Brad Rothenberg described as "computational geometry & design for additive manufacturing leader."
- Non-disruptive integration: drops into existing CAD workflows rather than replacing them, reducing switching friction.
- Strategic investor: Lockheed Martin as investor - validation and likely reference customer access in defense.
- No patent or IP count mentioned. No data moat or marketplace effects beyond the workflow flywheel.
Team & funding ask / use of funds
- Brad Rothenberg - Founder & CEO; computational geometry & design for additive manufacturing expert
- Steve Costello - CRO; built enterprise sales at Aras PLM, zCorp, SpaceClaim; defense experience at Digital Globe & BAE Systems
- Blake Courter - CTO; founded SpaceClaim; PM at PTC, GrabCAD, Stratasys
- George Allen - CSO; 40 years at Unigraphics/NX; pioneer in solid modeling; R&D, strategic planning, customer consulting
- Carl Bass - Independent Board Director; former CEO Autodesk (2006–2017)
- Investors: Canaan, Data Collective (DCVC), Root Ventures, Carl Bass, Haystack, Pathbreaker Ventures, Lockheed Martin
- Prior rounds: Not itemized in deck.
Recommended financial model
- Archetype + why: SaaS ARR land-and-expand model with seat-count driver. The business is pure B2B SaaS with a three-tier expansion motion (Land → Expand → Enterprise) and explicit ACV bands. The right model is a cohort-based ARR build: new logos land at small ACV, expand within 6–12 months, and compound toward $1M+ enterprise contracts. This maps cleanly to a logo cohort × ACV expansion waterfall.
- Forecast horizon & granularity: 5 years (2020–2024), quarterly for years 1–2, annual for years 3–5. Q1 2020 is the anchor point (>$2M ARR).
- Key drivers & assumptions:
| Driver | Value | Source |
|---|---|---|
| ARR at model start (Q1 2020) | $2.0M | - |
| ARR target end of 2020 | $5.0M | - |
| Monthly user growth rate (2020) | >40% | - |
| Land ACV | $15K–$40K; use $27.5K midpoint | - |
| Expand ACV | $100K–$500K; use $200K midpoint | - |
| Enterprise ACV | $1M+ floor; use $1.5M | - |
| 2019 blended ACV | $35.5K | - |
| 2020 blended ACV (early) | $25K | - |
| Land → Expand conversion timing | 6–12 months | - |
| Expand → Enterprise timing | >12 months from land | - |
| Land seat count | 2–6 users | - |
| Expand seat count | 20–100 users | - |
| Enterprise seat count | 125+ users | - |
| Pipeline Enterprise share | 58% | - |
| Pipeline Land share | 43% | - |
| Author / User split | 11% Authors, 89% Users | - |
| New logo adds per quarter (2020) | ~3–6 new logos/qtr; implied by pipeline volume ($1M–$3M by vertical) and $25K ACV | |
| Land → Expand conversion rate | 70%; strong product stickiness implied by case studies and retention claims | |
| Expand → Enterprise conversion rate | 30% of expanded accounts; enterprise is a subset | |
| Annual gross churn | <5%; engineering software with workflow lock-in typically very low churn; no figure given | |
| Net Revenue Retention | 130–150%; land-expand motion with 3–5× ACV expansion implies strong NRR | |
| Gross margin | 75–80%; typical B2B SaaS engineering software; no COGS data given | |
| Headcount growth | proportional to pipeline; sales team scale needed to hit $5M ARR |
- Scenarios (Base / Bull / Bear - which variables flex):
- Base: Land 4 logos/qtr in 2020; 70% L→E conversion at 9-month lag; gross churn 5%; NRR 135%. Hits ~$5M ARR by year-end 2020, consistent with deck target.
- Bull: Land 6 logos/qtr; 80% L→E conversion; NRR 150%; enterprise deals close faster. ARR reaches $8–10M by end of 2020.
- Bear: Pipeline slippage (only 2 logos/qtr landing); L→E conversion 50%; some churn on smaller accounts. ARR stalls at $3–3.5M by year-end 2020.
- Flex variables: new logo velocity, L→E conversion rate, enterprise ACV realization, monthly user growth (leading indicator of expansion revenue).
- Required sheets / outputs:
- Assumptions - all drivers in one place, color-coded inputs
- ARR Waterfall - starting ARR + new logos + expansion + churn = ending ARR, quarterly
- Logo Cohort Table - cohort by quarter; track each cohort's ACV progression Land→Expand→Enterprise over time
- User Count Build - monthly active users (Authors + Users) as leading pipeline indicator; ties to 40% monthly growth claim
- Revenue & P&L - ARR to recognized revenue; gross margin; operating expenses (R&D, S&M, G&A); EBITDA
- Pipeline Model - pipeline by stage × industry; close rates; bridge to new logo adds
- Headcount Plan - sales, engineering, CS headcount; comp assumptions
- Cash & Runway - cash burn vs. ARR milestone; implied raise sizing
- Scenario Toggle - dropdown or flag to switch Base / Bull / Bear
Frequently asked
Is the nTopology financial model free?+
Yes. The nTopology 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 nTopology'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 Hardware/Deep-tech Startup Financial Models
Browse another startup in the same category.
ANYbotics
ANYbotics builds and sells autonomous legged inspection robots (ANYmal) for industrial facilities, targeting oil & gas, chemicals, power, offshore, mining, and manufacturing sectors.
Awake Security
Awake Security - AI-driven Network Detection & Response (NDR) platform for the hybrid cloud, positioning as the "intent detection" layer of the SOC visibility triad.
Beem
AR communications platform that overlays full-body "hologram" video of a person into the recipient's physical space via smartphone or web.
Blue White Robotics
Autonomous robotics platform converting existing farm equipment to self-driving tractors for permanent-crop growers, sold as Robots-as-a-Service.
Cambridge GaN Devices
Fabless semiconductor startup commercialising self-protected GaN power transistors (HiGaN) that replace silicon and standard GaN with higher efficiency and no external protection circuitry.
Canix
Cannabis-focused ERP (inventory tracking, compliance automation, sales management, yield forecasting) sold as SaaS to cannabis cultivators, manufacturers, and distributors.
Chobani
Chobani is the US market leader in Greek yogurt; TPG invested $671M in April 2014 for a 35% stake via a structured second lien + equity deal
Cipher Skin
Wearable sensor mesh platform that collects dense multi-modal data from human bodies and industrial objects to predict structural and functional failure before it occurs.
