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Peak Financial Model

AI/ML Startup Financials (Free Excel Download)

Enterprise AI system platform that enables companies to ingest, transform, train, deploy, and action AI end-to-end in a single cloud-native product.

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About this model

Peak provides an end-to-end enterprise AI system spanning data ingestion, management, model building, training, deployment, prediction, decisions, and action. Built on AWS serverless infrastructure, Peak AI Studio lets users orchestrate visual workflows and access outputs through web applications or APIs.

The platform is sold as recurring enterprise software. By Q1 2020, the deck reported 140% year-on-year ARR growth, 79% gross margin, and a team approaching 125 people, although absolute ARR and customer figures were redacted.

The model uses an ARR waterfall for new enterprise logos, expansion, and churn, turning subscriptions into recognised revenue. It tests ACV, retention, cloud costs, sales productivity, R&D and operating headcount, gross margin, cash burn, and runway under high-growth and deceleration 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 Peak

peak.ai
Read the pitch deck
Peak pitch deck cover
View on makeslides.com
Total raised
$12.0M
Funding round
Seed
Founded
2020
Category
AI/ML
Customer
B2B
Geography
UK-headquartered

How to build a detailed financial model for Peak

A complete walkthrough of the business, drivers, and assumptions behind the downloadable Peak model - distilled from its pitch deck and publicly available information.

Product & value proposition

  • "Peak AI System": end-to-end enterprise AI platform covering data ingest, data management, model build/configure, training & deployment, prediction layer, decision layer, and action/integration layer.
  • Built on AWS serverless architecture for scale.
  • Outputs accessible via in-built web apps or API integrations.
  • Value prop: speed to value, reduced opportunity cost, optimises the whole value chain in one system - contrasted against expensive, slow self-build alternatives.
  • Branded interface: "Peak AI Studio" with visual workflow orchestration.

Revenue model

  • Annual recurring revenue (ARR) model - implied by the ARR metric reported.
  • Pricing structure, contract sizes, and go-to-market channels not disclosed.
  • Enterprise sales motion assumed given "enterprise AI system" positioning and customer base implied. Typical enterprise AI SaaS is annual/multi-year subscription, sold direct.

Traction & metrics

  • ARR: £xxm as of March 2020 - absolute value deliberately redacted.
  • ARR Growth: 140% YoY in Q1 2020.
  • Gross Margin: 79% in Q1 2020.
  • ARR chart: continuous upward trajectory from Jul-17 to Jan-20 (area chart, steep acceleration from mid-2019).
  • Headcount: growing steadily Jan-17 to Jan-20; y-axis appears to peak at ~125 employees by early 2020.
  • Team satisfaction: 4.7/5 in Q4 2019.
  • Glassdoor: 5.0 stars, 100% Recommend to a Friend, 100% Approve of CEO (Richard Potter), 12 ratings.
  • Attrition: 0% unwanted turnover in the past six months (0% in UK).
  • Sunday Times 100 Best Small Companies to Work For 2020.
  • Customer names, logo count, and NRR/churn not disclosed.

Unit economics

  • Gross Margin: 79% in Q1 2020.

Competition / moat

  • Slide 2 frames the problem space (data silos, no-AI-infrastructure, skills shortage, self-build). Positions Peak as the solution to self-build.
  • Slide 5 claims Peak is "the only product with an end-to-end AI capability, built specifically for the enterprise."
  • No explicit competitive landscape slide or named competitors.
  • Moat implied: end-to-end workflow lock-in, proprietary orchestration layer, AWS serverless infra, time-to-value advantage.

Team & funding ask / use of funds

  • CEO named: Richard Potter (inferred from Glassdoor CEO approval metric).
  • Headcount ~125 as of early 2020.
  • Team quality signalled via hiring growth, culture awards, and satisfaction scores; no named co-founders or exec bios shown in deck.

Recommended financial model

  • Archetype + why: SaaS ARR model with headcount-driven cost build. Peak is a pure B2B SaaS enterprise business with ARR, 79% gross margins, and 140% YoY ARR growth as its core KPIs - a standard SaaS ARR waterfall (new ARR + expansion - churn = ending ARR) is the correct frame. A light 3-statement overlay is warranted given the ~125-person headcount (OpEx/burn visibility matters for the fundraise).
  • Forecast horizon & granularity: 3 years monthly (2020–2022), rolling to annual for years 4–5. Monthly granularity needed to model ARR ramp, hiring plan, and burn.
  • Key drivers & assumptions:
DriverValue / Source
ARR as of March 2020£xxm - redacted; model as a placeholder input cell
ARR YoY growth (base)140% in Q1 2020; model forward as decelerating: 120% Y1, 90% Y2, 65% Y3
Gross margin79%; assume stable at 78–80%
New ARR split (new logo vs. expansion)70% new logo / 30% expansion; no NRR data in deck
Gross churn rate8–10% annual; enterprise SaaS benchmark; no data in deck
NRR~120% implied by growth + market; not disclosed
Average contract value (ACV)£150k–£300k; enterprise AI platform, UK HQ, mid-market to enterprise
Sales cycle3–6 months; typical enterprise AI
Headcount~125 as of early 2020; grow in line with ARR; assume R&D-heavy mix
Opex growth~60–70% YoY Y1, scaling down; majority is S&M and R&D payroll
Capex / infrastructureMinimal - AWS serverless; cloud COGS absorbed in gross margin
CurrencyGBP (peak.ai UK-HQ)
  • Scenarios (Base / Bull / Bear - which variables flex):
  • Bear: ARR growth decelerates faster (80% → 50% → 30%); gross churn 15%; hiring freeze.
  • Base: As above in assumptions table.
  • Bull: Growth sustains at 140% Y1, 110% Y2, 80% Y3; NRR 130%+; gross margin expands to 82%.
  • Flex variables: ARR growth rate, gross churn, ACV, headcount ramp.
  • Required sheets / outputs:
  1. Assumptions - all inputs centralised (ARR seed, growth, churn, GMs, headcount, ACV)
  2. ARR Waterfall - beginning ARR + new ARR + expansion - gross churn = ending ARR (monthly)
  3. P&L (Income Statement) - Revenue, COGS, Gross Profit, S&M, R&D, G&A, EBITDA, net loss
  4. Headcount Plan - by department (R&D, S&M, G&A); feeds into OpEx
  5. Cash Flow / Burn - operating cash burn, runway; critical for the fundraise context
  6. KPI Summary - ARR, MRR, ARR growth %, gross margin %, NRR, CAC, LTV, LTV:CAC, months of runway
  7. Scenario toggle - Bear / Base / Bull switcher feeding into all outputs

Frequently asked

Is the Peak financial model free?+

Yes. The Peak 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 Peak'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

Alex Tapio, ex-Deloitte financial modelling expert

Created by ex-finance professionals

Hey, I’m Alex and I created Finamodel.

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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.

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