# Keeyu Financial Model Build — LTM Actuals + NTM to A$5M ARR
**Source basis**: dataroom (`keeyu-dataroom-bb.md`), monthly management accounts Nov '25–Mar '26, internal ARR build (Jevon's tracker May '25–Jun '26), USA GTM deck
**Date**: 2026-04-15
**Audience for the resulting model**: Investor follow-up to dataroom review

---

## 0. How to read this document

This document is the **assumption layer and connective logic** behind the dataroom's headline numbers. Every figure used in the build is either (a) sourced from Xero / management accounts (LTM actuals), (b) sourced from the dataroom (top-down targets), or (c) explicitly derived here as a working assumption with a stated rationale.

Adam: when you build the spreadsheet, every assumption in this doc should become its own cell on an **Assumptions** tab so the model is fully driveable by changing inputs. Dollar figures are AUD unless flagged otherwise. **US revenue is treated 1:1 with AUD** (i.e. US$1,000 ACV is modelled as A$1,000) — this is a deliberate conservative simplification per Jevon. If FX moves materially we can layer a conversion line.

Recommended tab structure for the spreadsheet:
1. **Assumptions** — every driver below as a named cell
2. **LTM Actuals** — monthly P&L May '25–Apr '26
3. **Headcount** — hire-by-hire schedule with fully-loaded cost
4. **Sales Capacity** — SDR/AE funnel mechanics by month
5. **Customer Build** — new logos by channel + month, ARR build
6. **Expansion Waterfall** — grandfathered → rack-rate roll for existing 30
7. **Revenue Recognition** — contracted ARR vs billed revenue (with lag)
8. **NTM P&L** — full P&L May '26–Apr '27
9. **Cash Flow** — monthly with R&D rebates
10. **Summary** — one-page exec view

---

## 1. LTM Actuals (May '25 → Apr '26)

### 1.1 Monthly ARR trajectory (contracted)

Source: management accounts ARR chart + Jevon's customer-level monthly ARR tracker.

| Month | Contracted ARR | Net New ARR | # Customers | Notes |
|---|---|---|---|---|
| May '25 | A$97,200 | — | 8 | Baseline at start of LTM |
| Jun '25 | A$121,200 | +A$24,000 | 9 | Decjuba added at A$24K |
| Jul '25 | A$121,200 | +A$0 | 10 | Flat |
| Aug '25 | A$156,600 | +A$35,400 | 14 | New cohort onboarded |
| Sep '25 | A$164,400 | +A$7,800 | 15 | A Man & His Cave |
| Oct '25 | A$206,400 | +A$42,000 | 18 | Bronze Snake, Muscle Republic, Kivari |
| Nov '25 | A$227,400 | +A$21,000 | 19 | Pharmacy Online |
| Dec '25 | A$227,400 | A$0 | 19 | Holiday lull |
| Jan '26 | A$228,000 | +A$600 | 23 | Alternative Brewing/Desky AU at intro pricing |
| Feb '26 | A$382,020 | +A$154,020 | 28 | Desky USA, IM8 USA, Life Interiors, Mister Zimi, Okanui — first US wins |
| Mar '26 | A$606,120 | +A$224,100 | 34 | Boardriders A$61.8K, The Oodie A$90K, Puma A$30.6K, Elliatt A$17K, Petzyo |
| Apr '26 (est.) | A$817,000 | +A$210,880 | ~37 | Pipeline conversion in close stage |

**Assumption for Adam**: contracted ARR figures above are **month-end snapshots**. For monthly recognised revenue see §1.3.

### 1.2 Customer-level ARR tracker (May '25–Jun '26)

Full customer-by-customer monthly ARR build (30 customers, May '25 → Jun '26 actual+forecast) is in Jevon's source spreadsheet. Key shape:

- **Original 18 (grandfathered cohort)**: signed at intro pricing May–Nov '25. Mostly flat ARR through 2025, with **upsell events** beginning Jan–Mar '26 as the first tier upgrades fired (e.g. Budgy Smuggler A$3.6K → A$11.4K in Feb '26; EHP Labs A$18K → A$35.4K in Feb '26; Helly Hansen A$3.6K → A$18K → A$35.4K Jan-Mar '26).
- **11 new rack-rate customers**: signed Dec '25 → Mar '26 at full pricing. ACV range A$15K–A$90K, blended A$33,775.
- **Total LTM end-state (Apr '26)**: A$817K contracted ARR across 30 customers.

### 1.3 Monthly P&L — actuals (Nov '25 → Mar '26 detailed; May '25–Oct '25 see Xero)

Revenue line is **recognised (billed) revenue** — materially below contracted ARR/12 due to onboarding lag (typically signed M0, billed from M+1 or M+2).

| Line | Nov '25 | Dec '25 | Jan '26 | Feb '26 | Mar '26 |
|---|---|---|---|---|---|
| **Revenue (recognised)** | 12,492 | 13,742 | 13,742 | 17,259 | 18,658 |
| **COGS** | 9,784 | 9,502 | 11,098 | 12,832 | 15,799 |
| Cloud infra (Pump/AWS, DigitalOcean) | 9,090 | 9,489 | 10,642 | 10,779 | 10,678 |
| Merchant fees | 19 | 33 | 456 | 951 | ~270 |
| Model training (Claude.ai, Anthropic API) | 675 | -20 | 0 | 1,102 | 4,850 |
| **Gross Profit** | 2,708 | 4,240 | 2,644 | 4,428 | 2,859 |
| **GM %** | 21.7% | 30.9% | 19.2% | 25.7% | 15.3% |
| **Opex — Support/CS** | 10,500 | 8,400 | 8,400 | ~8,400 | ~8,400 |
| **Opex — GTM** | 39,440 | 50,016 | 42,486 | 36,852 | 49,161 |
|   GTM People (sal+super) | 26,165 | 29,534 | 31,554 | 28,325 | 28,700 |
|   GTM Software (subs) | 6,898 | 7,007 | 10,257 | 8,527 | 9,476 |
|   GTM Program (paid media, content) | 6,377 | 13,475 | 675 | 0 | 1,315 |
|   GTM Contractors | — | — | 6,353 | — | 9,695 |
| **Opex — P&E (R&D)** | 128,384 | 113,221 | 93,402 | 87,632 | 172,833 |
|   P&E People (sal+super) | 64,059 | 63,821 | 63,821 | 63,821 | 63,821 |
|   R&D Contractors | 64,325 | 49,400 | 29,581 | 23,100 | 48,700 |
|   P&E Software | — | — | — | — | 2,384 |
| **Opex — G&A** | 14,594 | 22,141 | 17,486 | 16,625 | 17,036 |
|   Rent | 3,921 | 11,232 | 4,580 | 4,580 | 4,580 |
|   Accounting/CFO | 4,050 | 4,050 | 4,050 | 4,050 | 2,750 |
|   Legal | 850 | 850 | 850 | 1,699 | 892 |
|   Co-wide software | 3,124 | 4,112 | 4,280 | 4,000 | 7,587 |
|   Insurance, travel, general, equipment | ~2,649 | ~1,897 | ~3,726 | ~2,296 | ~1,227 |
| **Total Opex** | 192,918 | 193,778 | 161,774 | 149,509 | 247,430 |
| **EBITDA** | (190,210) | (189,538) | (159,130) | (145,081) | (244,571) |
| **Net Income** | (187,052) | (185,666) | (155,077) | (142,173) | (200,578) |

> **Adam — for May '25–Oct '25 monthly P&L**: pull line-item detail from Xero. The chart of accounts above is the canonical structure (it matches the Quick Ratio CFO management account format). The **shape** of the early-LTM months is materially the same as Nov–Dec (lower revenue, similar P&E people cost ~A$60K/mo, lower R&D contractor spend, GTM ~A$30–40K/mo). For modelling purposes if you want a quick run-rate baseline: **avg LTM monthly opex Nov '25–Mar '26 = A$189,082/mo** ($945,409 / 5).

### 1.4 LTM Cash Trajectory

| Month | Opening Cash | Net Burn | R&D Rebate | Closing Cash |
|---|---|---|---|---|
| Nov '25 | A$1,332,811 | (A$197,978) | — | A$1,134,833 |
| Dec '25 | A$1,332,811 (revised post-recon) | (A$169,792) | — | A$1,163,019 |
| Jan '26 | A$1,163,019 | (A$171,127) | — | A$991,952 |
| Feb '26 | A$991,602 | (A$108,876) | — | A$882,624 |
| Mar '26 | A$882,624 | (A$200,150) | — | A$682,474 |
| Apr '26 (forecast) | A$682,474 | (~A$190,000) | +A$273,000 | A$765,474 |

R&D advance of **A$273K approved, expected April**. Second tranche of **A$273K forecast for Sep '26** (per Feb board report). A larger consolidated R&D claim is expected to land **M5 (Sep '26): A$500K** and **M11 (Mar '27): A$700K** per the dataroom forecast — these are rebate cycle peaks.

### 1.5 Headcount baseline (current, as of Apr '26)

Inferred from monthly P&L payroll lines and Mar '26 board commentary. **Adam — confirm against payroll roster.**

| Function | Headcount | Monthly cost (incl super) | Notes |
|---|---|---|---|
| Founders (Jevon CEO, Tracy CPO, Tahir CTO) | 3 | ~A$45,000/mo (combined) | Rough est; founders on reduced cash comp |
| Product & Engineering (perm) | 4–5 | A$63,821/mo total | Mar '26 P&L line: $56,983 sal + $6,838 super |
| GTM (perm — incl 1 SDR Louise) | 3 | A$28,700/mo total | Mar '26 P&L line: $25,625 sal + $3,075 super |
| Customer Success/Support | 1 | A$8,400/mo | Single hire flagged in Feb board report |
| **Permanent total** | **~12** | **~A$146,000/mo** | A$1.752M annualised perm payroll |
| R&D Contractors (IDP Solutions, Eritheia Labs, Muhammad Waleed, Ali Rehman Khan) | 4 | A$23K–A$49K/mo (variable) | Avg LTM ~A$32K/mo |
| GTM Contractors (Connor Johnston, Marketect Pro) | 1–2 | A$3K–A$10K/mo | Variable |

**Loaded cost multipliers to apply**:
- AU permanent: **1.25x base** (super 11.5% + payroll tax ~5.45% NSW + workers comp + tools/laptop)
- US permanent: **1.30x base** (employer FICA 7.65% + benefits ~10–15% + payroll tax + tools)
- Contractors (offshore IN/PK/AU): **1.0x** (gross invoice; no super/tax obligation)

---

## 2. NTM Build (May '26 → Apr '27) — Path to A$5M ARR

### 2.1 Headline targets (from dataroom)

| Milestone | Month | ARR target | Customer count |
|---|---|---|---|
| Starting ARR | May '26 (M0) | A$606K (Mar '26 contracted) — modelled A$817K opening assuming Apr '26 closes | 30 |
| M3 | Aug '26 | A$1.0M | ~50 |
| M6 | Nov '26 | A$1.9M | ~75 |
| M9 | Feb '27 | A$3.2M | ~110 |
| M12 | Apr '27 | A$5.0M | ~140 |

**Net new ARR required over NTM**: **A$4.4M** (from A$606K → A$5M; dataroom builds in A$350K buffer to A$4.75M new ARR).

**Channel mix of new ARR** (per dataroom):
- Direct (SDR/AE outbound): **43%** = A$1.892M new ARR
- Partnerships (agency/co-sell): **33%** = A$1.452M
- Inbound (organic, content, brand): **24%** = A$1.056M

**Expansion ARR (within existing 30)**: from §2.6 — modelled as ramp from grandfathered rates to rack rate, completing by Jan '27 (best case per Jevon). Adds ~A$200K of ARR not from new logos.

### 2.2 Sales Capacity Model — Direct channel (SDR/AE outbound)

This is the **mechanical engine** that translates headcount into ARR.

#### 2.2.1 SDR funnel assumptions

| Stage | Rate | Source/rationale |
|---|---|---|
| Dials per SDR per day | **200** | Jevon's gut + autodialer-supported pace; Outreach.io/Salesloft benchmark cite 150–250 with parallel dialers. **Aggressive but achievable** with tooling already in stack (Freckle, Sure Connect, Instantly). |
| Working days per month | **20** | Standard; excludes leave |
| Total dials/SDR/month | **4,000** | 200 × 20 |
| Connect rate (live conversation) | **5%** | Cold-call SaaS ANZ benchmark 4–7%; B2B e-commerce decision-maker reachability lower than horizontal SaaS |
| Connects/SDR/month | **200** | 4,000 × 5% |
| Meeting-booked rate (per connect) | **15%** | Industry: 10–20% for warm scripts on outbound; Keeyu's value prop (CX cost reduction) is qualified pain |
| Meetings booked/SDR/month | **30** | 200 × 15% |
| Show rate (booked → held disco) | **65%** | Standard; SaaS no-show rate 30–40% |
| Discos held/SDR/month | **~20** | 30 × 65% |

> **Adam — sensitivity to model**: a 20% miss on connect rate (4% vs 5%) drops monthly discos from 20 to 16. A 20% miss on dials (160/day vs 200) drops monthly discos from 20 to 16 also. These are the two highest-leverage drivers — flag them as top assumptions on the Assumptions tab.

#### 2.2.2 AE funnel assumptions

| Stage | Rate | Source/rationale |
|---|---|---|
| AE capacity (discos held/month) | 20 | Matches one SDR's output → **1 SDR : 1 AE pod ratio** |
| Disco → Demo conversion | **60%** | Industry 50–70%; Keeyu's discovery is structured (pain points doc, mutual action plan) so trending high end |
| Demos held/AE/month | **12** | 20 × 60% |
| Demo → Won (close) conversion | **30%** | Industry 20–40% for mid-market SaaS; Keeyu's existing pipeline shows 4 of 10 Won from Demo+Close stage in Mar '26 board report |
| Wins/AE pod/month | **~3.6** | 12 × 30% |
| Sales cycle (disco → signed) | **30–45 days** (use 38d midpoint) | Per Jevon. Validates against deal-flow folder evidence: Puma 5-Feb disco → close call 25-Feb (20d), The Oodie 9-Feb disco → contract 27-Feb (18d), Boardriders 17-Feb intro → 26-Mar contract (37d) |
| Average ACV (new logo) | **A$35,000** | Recent 11-customer cohort blended A$33,775; dataroom builds at A$35K-A$57K range with US deals trending higher |

**Direct channel monthly contribution per AE pod (1 SDR + 1 AE)**:
- Steady-state: 3.6 wins × A$35K = **A$126,000 new ARR / pod / month**
- Ramp: AE/SDR new hires take **2 months to ramp** (M+1 prospecting only, M+2 first deals close). Apply 0%, 33%, 67%, 100% productivity in months 1, 2, 3, 4+.

#### 2.2.3 Direct channel headcount plan

To deliver A$1.892M Direct ARR over 12 months:
- Required pod-months at full productivity = A$1,892,000 / A$126,000 = **15 pod-months equivalent**
- With ramp curve, plan **3 pods active at full productivity by M3**, scaling to **4 pods by M6**.

| Hire timing | Role | Region | Month |
|---|---|---|---|
| M1 (May '26) | US AE #1 | US | Pod 1 lead (US) |
| M1 | US SDR #1 | US | Supports US AE |
| M1 | AU SDR #2 | AU | Supports existing AU AE/founder selling |
| M2 (Jun '26) | US AE #2 | US | Pod 2 |
| M2 | US SDR #2 | US | Supports US AE #2 |
| M5 (Sep '26) | US AE #3 | US | Pod 3 |
| M5 | US SDR #3 | US | Supports US AE #3 |
| M8 (Dec '26) | AU AE #2 | AU | Backfill AU coverage |
| M8 | AU SDR #3 | AU | Supports AU AE #2 |

### 2.3 Partnerships channel (33% / A$1.452M new ARR)

Partnership programme is in early build (per memory: AU agency partner programme launching, partner Slack, PAS scoring of 3 agency buckets). **Ramp curve**: assume partnerships contribute A$0 in M1–M2 (relationship build), then ramp linearly to ~A$160K/month by M9 and hold.

**Capacity assumptions**:
- US Partnerships Manager hired **M1 (May '26)**, fully ramped by M3
- AU partnerships managed by founder until M6
- Each agency partner referral generates **2–3 deals per quarter at A$35K ACV**
- Target: **20 active referring agencies by M12** (US + AU)
- Implied: 20 partners × 2.5 deals/qtr × A$35K = A$1.75M annualised — gives A$1.452M target with buffer for ramp

### 2.4 Inbound channel (24% / A$1.056M new ARR)

Inbound = organic search, content, brand-led, podcast, referral.

**Capacity assumptions**:
- Inbound MQL → SQL conversion: 30%
- SQL → Won: 25%
- Required wins: A$1.056M / A$35K = **30 wins over 12 months = ~2.5/month avg**
- Required SQLs: 30 / 25% = **120 SQLs over 12 months = 10/month**
- Required MQLs: 120 / 30% = **400 MQLs over 12 months = ~33/month**

**Content/brand investment to drive this**:
- **US Marketing Manager hired M2** (drives US-relevant content, paid acquisition, brand)
- **AU Content/SEO contractor maintained** (currently Connor Johnston / Neon Deer Data Labs)
- **Paid program spend ramp**: A$5K (M1) → A$20K/month by M6 → A$30K/month by M12. Total NTM paid spend: ~A$240K
- Implied **inbound CAC**: A$240K / 30 wins = A$8,000 per win, against A$35K ACV — well within healthy SaaS LTV:CAC

### 2.5 Customer ramp + billing lag

Critical mechanic: **contract signed in M0 → first invoice raised in M+2** (45-day onboarding/integration period before billing commences). Monthly billing in advance, no annual prepay, no setup fee.

**Implication for revenue recognition**:
- A deal signed in May '26 (M1) generates **recognised revenue from Jul '26 (M3)** onward
- Therefore **billed revenue lags contracted ARR by ~2 months**

**Worked example**:
- M1 wins: 0 (no AEs yet ramped; existing pipeline conversions only)
- M2 wins: ~3 logos × A$35K = A$105K contracted ARR; first billed M4 → adds A$8.75K MRR from Jul
- M3 wins: ~7 (2 pods at 33%/67% ramp); A$245K contracted; billed M5 → A$20.4K MRR from Aug
- M6 wins: ~12 (3 pods full prod + 1 ramping); A$420K contracted; billed M8 → A$35K MRR
- ...etc.

### 2.6 Expansion waterfall — existing 30 customers

The original 18 grandfathered customers are at **A$209K contracted (Jan '26)** vs **A$488K rack rate** = **A$279K of unrealised expansion**.

**Per Jevon (Apr '26)**: best-case full migration to rack rate is **complete by Jan '27 (M9)**. Migration is **slower than dataroom assumed** — driven by retention sensitivity and the need to deliver tier-upgrade value before pricing change.

**Modelled monthly expansion ARR uplift** (additive to new logos):
| Month | Cumulative expansion captured | Notes |
|---|---|---|
| May '26 (M1) | A$0 | Apr '26 ARR baseline already includes ~A$74K of expansion captured Jan-Apr '26 |
| Jun '26 (M2) | A$10K | First scheduled rack-rate conversions |
| Sep '26 (M5) | A$60K | Steady migration |
| Dec '26 (M8) | A$140K | Acceleration |
| Jan '27 (M9) | A$200K | **Full grandfathered cohort migrated to rack rate** |
| Apr '27 (M12) | A$200K | Plus tier upgrades on the 11 rack-rate customers — ~A$30K more |

**Total expansion contribution to A$5M target**: ~**A$230K**, which is modest relative to A$4.4M from new logos. This is conservative — if migration accelerates, upside.

**No tier-upgrade journey on new wins**: per Jevon, all new sign-ups go straight onto **Automate** tier. This means **higher initial ACV** (A$35K avg) but **less expansion runway** within the new cohort.

### 2.7 Churn assumption (revised — per Jevon sign-off Apr '26)

**0% churn through M7 (Nov '26)**. From **M8 (Dec '26) onward: 5% annual churn rate** = ~0.42% monthly applied to the total contracted ARR base.

This reflects: (a) LTM zero churn maintained through early NTM scale-up, (b) realistic expectation that at 80+ customers some will not renew, and (c) BB-defensible — proactively modelling churn rather than claiming zero forever.

**Monthly churn impact (M8–M12)**:

| Month | Starting ARR | Monthly churn (0.42%) | Churn A$ |
|---|---|---|---|
| M8 Dec '26 | ~A$2,974K | -A$12,400 | |
| M9 Jan '27 | ~A$3,455K | -A$14,400 | |
| M10 Feb '27 | ~A$3,952K | -A$16,500 | |
| M11 Mar '27 | ~A$4,481K | -A$18,700 | |
| M12 Apr '27 | ~A$5,057K | -A$21,100 | |
| **Total M8–M12** | | | **-A$83,100** |

> **Adam**: model churn as a cell on the Assumptions tab. Apply monthly (5%/12 = 0.417%) against total contracted ARR from M8 onward. This reduces ending ARR by ~A$83K.

### 2.8 NRR

Existing dataroom: **108% NRR** (current). Modelled NRR in NTM = **125%** (driven by grandfathered → rack rate roll). Reverts to ~115% steady-state post-Jan '27.

---

## 3. Headcount Schedule (NTM hire-by-hire)

### 3.1 Salary bands (researched; AUD; **fully-loaded**)

US bands sourced from levels.fyi / Pave 2025 SaaS Series A medians, then converted to AUD at 1:1 per Jevon convention.

| Role | Region | Base salary (AUD) | Loaded multiplier | **Fully-loaded annual** | **Monthly** |
|---|---|---|---|---|---|
| US AE | US | A$90,000 base (US$90K) + A$90,000 variable → A$180K OTE | 1.30x on base, plus full variable | **A$207,000** | A$17,250 |
| US SDR | US | A$80,000 base + A$30K variable → A$110K OTE | 1.30x | **A$130,000** | A$10,833 |
| AU AE | AU | A$110,000 base + A$65K variable → A$175K OTE | 1.05x (super on base + tools) | **A$185,000** | A$15,417 |
| AU SDR | AU | A$70,000 base + A$25K variable | 1.25x | **A$112,500** | A$9,375 |
| US Partnerships Manager | US | A$160,000 base + A$60K bonus | 1.30x | **A$240,000** | A$20,000 |
| US Marketing Manager | US | A$150,000 base | 1.30x | **A$195,000** | A$16,250 |
| AI Engineer #1 | AU/Remote | A$180,000 base | 1.25x | **A$225,000** | A$18,750 |
| AI Engineer #2 | AU/Remote | A$170,000 base | 1.25x | **A$212,500** | A$17,708 |
| Customer Success Manager #1 | AU | A$110,000 base | 1.25x | **A$137,500** | A$11,458 |
| Customer Success Manager #2 (US) | US | A$120,000 base | 1.30x | **A$156,000** | A$13,000 |
| Implementation Engineer | AU | A$130,000 base | 1.25x | **A$162,500** | A$13,542 |

### 3.1.1 US AE compensation — market research + options for Jevon sign-off

**Per Jevon Apr '26**: "A$300K OTE is no way. That's double what the founders earn. Do more market research." Below are the findings.

**2025–2026 US AE compensation benchmarks** (mid-market B2B SaaS, ACV US$30K–60K range):

| Source | Base (US$) | OTE (US$) | Notes |
|---|---|---|---|
| Bridge Group 2024 Benchmarks | US$75–95K | US$140–200K | Mid-market segment; 50/50 base:variable split |
| RepVue (2026 national median) | US$100K | US$195K | Broad SaaS AE median |
| Everstage SaaS Compensation | US$75–90K | US$140–180K | Series A / early-stage focus |
| Salary.com (SF/NY) | US$100K | US$200–250K | Premium markets only |
| Tier-2 markets (Austin, Denver, remote) | US$70–85K | US$140–170K | Lower COL |

**Key finding**: US$300K OTE (= A$300K at 1:1) is **top-of-market for late-stage Series C+ companies**, not early-stage Series A. For a Series A company selling A$35K ACV deals, the realistic range is **US$140K–US$200K OTE**.

**Three options for Jevon**:

| Option | Base (US$) | Variable (US$) | OTE (US$) | OTE (A$) | Fully loaded (A$) | Monthly |
|---|---|---|---|---|---|---|
| **A — Conservative** | US$80K | US$80K | US$160K | A$160K | A$184K | A$15,333 |
| **B — Mid-market** | US$90K | US$90K | US$180K | A$180K | A$207K | A$17,250 |
| **C — Competitive (SF/NY)** | US$100K | US$100K | US$200K | A$200K | A$230K | A$19,167 |

Loaded = base × 1.30 (employer FICA, benefits, payroll tax) + full variable.

**Recommendation**: **Option B (A$180K OTE / US$180K OTE)** — mid-market for Series A, competitive enough to attract strong AEs without the SF premium. Remote-first or Tier-2 city hires.

**Quota:OTE ratio**: at Option B, quota A$1.0M / OTE A$180K = **5.6:1** (industry median 4.2:1 per Bridge Group). At industry-standard 4.2:1 ratio, quota would be A$756K (= 18 deals × A$42K ACV or 21 deals × A$36K ACV). **At 4 wins/mo × 12 × A$35K = A$1.68M closed, the AE is at 222% quota — variable comp maxes out.** Consider quota of A$1.2M with 50/50 split and 1.5x accelerator above 100%.

> **Jevon — pick A, B, or C**. This decision affects cumulative NTM payroll by ~A$120K (3 US AEs × 12 months × ~A$3K/mo delta between options). No wrong answer at these ranges.

### 3.2 Hire schedule (revised — 2 SDRs per AE, first start M3 Jul '26)

Per Jevon Apr '26: **no hires start before M3.** Each AE pod = 1 AE + 2 SDRs. AU SDR #2 supports Louise/Jevon; US Pods each get 2 dedicated SDRs; AU Pod 2 gets 2 dedicated SDRs.

| Month | Hire | Region | Annual loaded cost | Cumulative monthly payroll add |
|---|---|---|---|---|
| **M3 Jul '26** | US AE #1 | US | A$207,000 | +A$17,250 |
| M3 | US SDR #1a (Pod 1) | US | A$130,000 | +A$10,833 |
| M3 | US SDR #1b (Pod 1) | US | A$130,000 | +A$10,833 |
| M3 | AU SDR #2 (supports Louise/Jevon) | AU | A$112,500 | +A$9,375 |
| M3 | US Partnerships Manager | US | A$240,000 | +A$20,000 |
| **M3 monthly add: A$68,291** | | | **A$819,500/yr** | |
| **M4 Aug '26** | US Marketing Manager | US | A$195,000 | +A$16,250 |
| M4 | AI Engineer #1 | AU | A$225,000 | +A$18,750 |
| **M4 monthly add: A$35,000** | | | **A$420,000/yr** | |
| **M6 Oct '26** | US AE #2 (Pod 2) | US | A$207,000 | +A$17,250 |
| M6 | US SDR #2a (Pod 2) | US | A$130,000 | +A$10,833 |
| M6 | US SDR #2b (Pod 2) | US | A$130,000 | +A$10,833 |
| M6 | Customer Success Manager #1 | AU | A$137,500 | +A$11,458 |
| **M6 monthly add: A$50,374** | | | A$604,500/yr | |
| **M7 Nov '26** | Implementation Engineer | AU | A$162,500 | +A$13,542 |
| **M7 monthly add: A$13,542** | | | A$162,500/yr | |
| **M9 Jan '27** | AI Engineer #2 | AU | A$212,500 | +A$17,708 |
| **M9 monthly add: A$17,708** | | | A$212,500/yr | |
| **M10 Feb '27** | AU AE #2 (AU Pod 2) | AU | A$185,000 | +A$15,417 |
| M10 | AU SDR #3a (AU Pod 2) | AU | A$112,500 | +A$9,375 |
| M10 | AU SDR #3b (AU Pod 2) | AU | A$112,500 | +A$9,375 |
| **M10 monthly add: A$34,167** | | | A$410,000/yr | |
| **M12 Apr '27** | Customer Success Manager #2 | US | A$156,000 | +A$13,000 |
| **M12 monthly add: A$13,000** | | | A$156,000/yr | |

**Cumulative new hires payroll by M12**: **+A$256,582/month** = A$3.079M annualised (vs A$233,289/mo before adding extra SDRs — net +A$23,293/mo for 3 extra SDRs).

**Total perm payroll by Apr '27 (M12)**: A$146,000 (existing) + A$232,082 (new) = **A$378,082/month** = A$4.54M annualised.

> US AE cost dropped from A$354K to A$207K loaded (Option B confirmed). Saves A$147K/yr per US AE × 2 = **A$294K/yr NTM payroll savings** vs prior draft.

> **Important**: variable comp (AE/SDR commissions) is included in the OTE-based loaded numbers above — this assumes 100% quota attainment. Apply a **75% attainment factor** for budgeting prudence. If you want a separate "commission accrual" line, model 12% of new ARR as commission expense in the month signed.

### 3.3 Existing payroll (May '25 → Apr '26 baseline)

Per management accounts:
- 9-month total people cost (P&E + GTM + Support, Aug '25–Apr '26): roughly $100K/mo × 9 = A$900K
- Annualised baseline = A$1.20M / yr permanent + ~A$380K/yr R&D contractors = **A$1.58M LTM total payroll cost**

NTM should hold contractor spend roughly flat (~A$30K/mo) while perm headcount adds.

---

## 4. Month-by-Month Build — Capacity → Wins → ARR

This is the **operating heart** of the model: every month, we have a specific number of producing SDRs and AEs, with each at a specific point on their ramp curve. That headcount produces a specific number of dials, meetings, discos, demos, and wins. Wins × ACV = new contracted ARR. New contracted ARR + lag = recognised revenue.

### 4.1 Productivity assumptions (the levers)

**SDR funnel** (per Jevon Apr '26 calibration):
| Step | Rate | Calc |
|---|---|---|
| Dials/SDR/day | 200 | |
| Working days/mo | 20 | |
| **Dials/SDR/month** | **4,000** | 200 × 20 |
| × Connect rate | **10%** | |
| **Connects/SDR/mo** | **400** | |
| × Meeting-booked per connect | **10%** | (= 1 meeting per 100 dials) |
| **Meetings booked/SDR/mo** | **40** | |
| × Show rate | 65% | |
| **Discos held/SDR/mo** | **~26** | |

**Pod structure: 2 SDRs per 1 AE** (per Jevon — high-velocity outbound model, justified by ACV > A$30K).

**AE full-productivity output** (with 2 SDRs feeding) — using **Keeyu YTD Jan–mid-Apr '26 actual pipeline conversion rates** (n=76 opportunities):

| Step | Rate | Calc | Source |
|---|---|---|---|
| Discos delivered by 2 SDRs/mo | 52 | 26 × 2 | |
| AE absorption capacity (max realistic, parallel scheduling + SE support) | ~30 discos | bottleneck | |
| × Disco → Demo conversion | **64.47%** | 49/76 YTD | **YTD actual** |
| **Demos held/AE/mo** | **~19** | 30 × 64.47% | |
| × Demo → Close-stage conversion | **80.30%** | 53/66 YTD | **YTD actual** |
| **At Close stage/AE/mo** | **~15.5** | 19 × 80.30% | |
| × Close → Won conversion | **25.00%** | 11/44 YTD | **YTD actual** |
| **Wins/AE/mo at full productivity** | **~3.9 (round to 4)** | 15.5 × 25% | |

**Overall Disco → Won**: 14.5% (64.47% × 80.30% × 25%) — **YTD actual** vs prior industry benchmark of 13.6%. The slightly higher actual rate means the model is defensibly conservative even at 4 wins/AE/mo rounded.

> The 2:1 SDR:AE ratio + YTD-actual conversions produces ~4 wins/mo per AE at full productivity. One extra SDR per pod (A$130K US / A$112K AU loaded) buys A$840K extra ARR/yr per pod (4 vs 2 wins × 12 × A$35K) — extremely accretive.

**Annual per-AE math**: 4 wins/mo × 12 = **48 deals/yr × A$35K = A$1.68M/AE/yr** = quota likely set at A$1.5M with strong commission upside above. **OTE structure may need to reflect this** — current US AE OTE A$300K assumes ~A$1.0M quota; at A$1.5M quota, OTE should be ~A$360K (US$240K) to maintain quota:OTE ratio.

**Outcome rates (YTD context)** — worth noting for BB if probed on pipeline quality:
- Lost: 9.21% of total opps (7/76)
- No Fit: 17.11% (13/76)
- Pause: 17.11% (13/76)
- Won: 14.47% (11/76, same as Disco→Won calc above)

The 17% "Pause" rate is worth flagging — it's pipeline temporarily stalled (budget freeze, internal reorg, etc.) that may re-open. If even half of paused opps convert later, effective Won rate trends to ~17% overall.

**Ramp curve** (months 1, 2, 3, 4+ from hire start):
- AE: 0%, 25%, 50%, 100%
- SDR: 25%, 75%, 100%

**Hiring timing — important constraint** (per Jevon Apr '26 update): **no hires start before M3 (Jul '26)**. Recruitment opens M2 (Jun '26), all M3-cohort hires onboard M3. All subsequent hire dates also shift forward by 2 months from earlier draft.

**Existing pre-NTM team** (April '26 baseline):
- **Jevon** (founder selling): producing ~2.5 wins/mo from existing pipeline + outbound. Geography split: **AU-focused M1–M2** (closing existing AU pipeline, no hires yet), **US-focused M3 onwards** (in-market when US AE #1 starts; supports US Pod 1 ramp), **CEO/fundraise mode M9+** (only strategic deals).
- **Louise** (existing AU SDR): 100% productive, supplies ~20 discos/mo. Stays on **AU territory throughout** — feeds Jevon M1–M2, queues pipeline for AU Pod 2 from M10.
- **Tracy is NOT modelled in sales** — CPO, full-time on product. Zero AE attribution.

### 4.1.2 Source: Keeyu YTD pipeline conversion analysis (Jan → mid-Apr 2026)

Every conversion rate used in §4.1 is drawn from Keeyu's actual YTD pipeline (n=76 opportunities). This is not industry benchmark data — it is Keeyu's real funnel measured across Jan–mid-April 2026.

**Conversion Rates**
- **Disco → Demo Conversion Rate: 64.47%** (49 opportunities converted to Demo out of 76 total opportunities)
- **Demo → Close Conversion Rate: 80.30%** (53 opportunities at or past the Close stage out of 66 opportunities at or past the Demo stage)
- **Close → Won Conversion Rate: 25.00%** (11 'Won' opportunities out of 44 total closed opportunities, which includes Won, Lost, No Fit, and Pause statuses)

**Outcome Rates (as a percentage of the total 76 opportunities)**
- **Lost Rate: 9.21%** of total opportunities are 'Lost' (7 opportunities)
- **No Fit Rate: 17.11%** of total opportunities are 'No Fit' (13 opportunities)
- **Pause Rate: 17.11%** of total opportunities are on 'Pause' (13 opportunities)
- **Won Rate: 14.47%** of total opportunities are 'Won' (11 opportunities; same as end-to-end Disco → Won)

**Assumptions underpinning these conversion calculations**
- **Disco → Demo**: assumes the 76 rows represent the total opportunities that reached the Disco stage, and the `Disco Convert to Demo` column explicitly defines which opportunities moved to Demo.
- **Demo → Close**: assumes the pipeline flow is Disco → Demo → Close, and that all current statuses except 'Disco' have passed the Demo stage, and all current statuses in {Close, Won, Lost, No Fit, Pause} have passed the Demo stage and reached the Close stage.
- **Close → Won**: assumes that the outcomes {Won, Lost, No Fit, Pause} represent all fully closed deals, and the denominator is the sum of these four outcomes.

**Note on Pause rate (upside lever)**: 13 of 76 opportunities (17.1%) are currently paused — pipeline temporarily stalled (budget freeze, internal reorg, timing) that may re-open. If even half of paused opps eventually convert to Won, the effective Close → Won rate lifts from 25% toward ~31%, and overall Disco → Won lifts from 14.5% toward ~17.9%. This is a realistic upside not currently modelled.

### 4.1.1 Cold-call service (outsourced lead-gen, short-term bridge only)

**Short-term bridge only — NOT a long-term sales channel.** Per Jevon Apr '26: cold-call agency runs staggered by region, exits as soon as in-house SDRs ramp.

**Region-specific timing** (per Jevon sign-off):
- **AU**: Apr (pre-NTM), May (M1), Jun (M2) — 3 calendar months. Exits M2 as AU SDR #2 (hired M3) ramps.
- **US**: Jun (M2), Jul (M3), Aug (M4) — 3 calendar months. Starts later because US is secondary market until Jevon shifts US-focus M3. Exits M4 as US SDR #1a/b (hired M3) reach 75% ramp.
- **Overlap month**: Jun (M2) only — both regions running concurrently = A$8K that month.

| NTM Month | AU service | US service | Monthly cost |
|---|---|---|---|
| M1 May '26 | Running | — | A$4,000 |
| M2 Jun '26 | Running | Running | A$8,000 |
| M3 Jul '26 | Exited | Running | A$4,000 |
| M4 Aug '26 | — | Running (final month) | A$4,000 |
| **Total NTM** | | | **A$20,000** |

- Cost: **US$4,000 per region per month = A$4K per region per month**
- Productivity per region: ~10 discos/mo delivered (50% of in-house SDR; agency less effective at qualification)
- AU disco contribution: M1–M2 = 20 discos for Jevon (AU-focused)
- US disco contribution: M2–M4 = 30 discos for Jevon (US-focused) + US AE #1 (ramping M3+)
- **Total NTM disco contribution**: ~50 discos → ~7 captured wins
- **Why**: M1–M2 there are no new SDRs in seat; cold-call service fills the US funnel before hires arrive M3 and gives AU coverage while AU SDR #2 ramps.

**ACV blended for new logos**: A$35,000 (recent 11-customer rack-rate cohort = A$33,775; modelled at A$35K).

### 4.2 Direct channel: monthly capacity — **strictly staggered to hire dates, by AE producing wins**

Each cell = wins attributable to that AE in that month. **No AE produces wins before their hire date OR before they have ramped.** Cold-call service feeds wins to Jevon and US AE #1 during ramp.

**AEs identified (revised hire dates)**:
- **Jevon** (existing): AU-focused M1–M2 (2.5 wins), US-focused M3–M8 (1.5 wins from US, residual AU), CEO/fundraise M9+ (0.5 wins).
- **Louise** (existing AU SDR): feeds Jevon AU M1–M2; supports AU Pod 2 from M10.
- **US AE #1**: hired **M3 (Jul '26)**, ramps M3 (0%) → M4 (25%) → M5 (50%) → M6+ (100%).
- **US SDR #1**: hired M3, ramps M3 (25%) → M4 (75%) → M5+ (100%).
- **AU SDR #2**: hired M3, ramps M3 (25%) → M4 (75%) → M5+ (100%). Pipeline absorbed by Jevon until AU Pod 2 arrives.
- **US AE #2** = **"Pod 2"** — hired **M6 (Oct '26)**, ramps M6 (0%) → M7 (25%) → M8 (50%) → M9+ (100%).
- **US SDR #2**: hired M6, ramps M6 (25%) → M7 (75%) → M8+ (100%).
- **AU AE #2** = **"AU Pod 2"** — hired **M10 (Feb '27)**, ramps M10 (0%) → M11 (25%) → M12 (50%) → past NTM end (100%).
- **AU SDR #3**: hired M10, ramps M10 (25%) → M11 (75%) → M12 (100%).

**Each AE pod = 1 AE + 2 SDRs**. Jevon (founder) keeps Louise as his single SDR (founder-led, pre-NTM economics).

| Month | Jevon (AU) | Jevon (US) | US AE #1 (4/mo full) | US AE #2 / Pod 2 (4/mo full) | AU AE #2 (4/mo full) | Cold-call svc bonus | **Direct wins/mo** |
|---|---|---|---|---|---|---|---|
| **M1 May '26** | 2.5 | 0 | — (not hired) | — | — | 0.5 | **3.0** |
| **M2 Jun '26** | 2.5 | 0 | — | — | — | 1.0 | **3.5** |
| **M3 Jul '26** | 1.5 | 1.0 | 0 (onboarding) | — | — | 1.0 | **3.5** |
| **M4 Aug '26** | 1.0 | 1.5 | 1.0 (25%) | — | — | 0.5 | **4.0** |
| **M5 Sep '26** | 1.0 | 1.5 | 2.0 (50%) | — | — | 0 | **4.5** |
| **M6 Oct '26** | 0.5 | 1.5 | 4.0 (100%) | 0 (hired, onboarding) | — | 0 | **6.0** |
| **M7 Nov '26** | 0.5 | 1.5 | 4.0 | 1.0 (25%) | — | 0 | **7.0** |
| **M8 Dec '26** | 0.5 | 1.0 | 4.0 | 2.0 (50%) | — | 0 | **7.5** |
| **M9 Jan '27** | 0.5 | 0.5 | 4.0 | 4.0 (100%) | — | 0 | **9.0** |
| **M10 Feb '27** | 0.5 | 0.5 | 4.0 | 4.0 | 0 (hired, onboarding) | 0 | **9.0** |
| **M11 Mar '27** | 0 | 0.5 | 4.0 | 4.0 | 1.0 (25%) | 0 | **9.5** |
| **M12 Apr '27** | 0 | 0.5 | 4.0 | 4.0 | 2.0 (50%) | 0 | **10.5** |
| **NTM TOTAL** | 11.0 | 9.0 | 31.0 | 19.0 | 3.0 | 3.0 | **77.0 wins** |

**Direct channel result**: **77 wins × A$35K = A$2.695M new ARR** over NTM.

This is **143% of the dataroom 43% direct target (A$1.89M)** — A$805K buffer above plan. The combination of 2:1 SDR:AE + 80% disco→demo more than compensates for the M3 hire delay.

> **Pod 2 = US Pod 2 = US AE #2 + 2 US SDRs** hired **M6 Oct '26**.

### 4.3 Partnerships channel: monthly capacity (revised — hire delay)

US Partnerships Manager now hired **M3** (was M1). AU partner programme (TalentPop + Keeyu agency motion) starts ramping from M3 but with founder oversight only until US PM is in seat.

| Month | Active referring agencies | Wins/mo | **Partnership ARR/mo (A$35K)** |
|---|---|---|---|
| M1 May '26 | 1 (early AU founder-led) | 0.2 | A$7,000 |
| M2 Jun '26 | 1 | 0.2 | A$7,000 |
| M3 Jul '26 | 1 (PM onboarding) | 0.2 | A$7,000 |
| M4 Aug '26 | 2 | 0.5 | A$17,500 |
| M5 Sep '26 | 3 (TalentPop signs) | 0.7 | A$24,500 |
| M6 Oct '26 | 4 | 1.0 | A$35,000 |
| M7 Nov '26 | 5 | 1.3 | A$45,500 |
| M8 Dec '26 | 6 | 1.5 | A$52,500 |
| M9 Jan '27 | 7 | 1.8 | A$63,000 |
| M10 Feb '27 | 8 | 2.0 | A$70,000 |
| M11 Mar '27 | 9 | 2.3 | A$80,500 |
| M12 Apr '27 | 10 | 2.5 | A$87,500 |
| **NTM TOTAL** | | **14.2 wins** | **A$497,000** |

**Partnership channel result**: **14 wins × A$35K = A$497K new ARR**. Materially below dataroom 33% target.

### 4.4 Inbound channel: monthly capacity (revised — hire delay)

US Marketing Manager now hired **M4** (was M2). M1–M3 inbound runs on existing organic + Connor Johnston content output only.

| Month | MQLs/mo | SQLs/mo (×30%) | Wins/mo (×25%) | **Inbound ARR/mo (A$35K)** |
|---|---|---|---|---|
| M1 May '26 | 12 | 3 | 0.8 | A$28,000 |
| M2 Jun '26 | 13 | 4 | 0.9 | A$31,500 |
| M3 Jul '26 | 15 | 4 | 1.0 | A$35,000 |
| M4 Aug '26 | 18 | 5 | 1.3 | A$45,500 |
| M5 Sep '26 | 22 | 7 | 1.7 | A$59,500 |
| M6 Oct '26 | 28 | 8 | 2.1 | A$73,500 |
| M7 Nov '26 | 34 | 10 | 2.5 | A$87,500 |
| M8 Dec '26 | 40 | 12 | 3.0 | A$105,000 |
| M9 Jan '27 | 44 | 13 | 3.3 | A$115,500 |
| M10 Feb '27 | 48 | 14 | 3.6 | A$126,000 |
| M11 Mar '27 | 50 | 15 | 3.8 | A$133,000 |
| M12 Apr '27 | 52 | 16 | 4.0 | A$140,000 |
| **NTM TOTAL** | | | **28.0 wins** | **A$980,000** |

**Inbound channel result**: 28 wins × A$35K = **A$980K new ARR**. Slightly below dataroom 24% target (A$1.06M).

### 4.5 Combined new ARR build by month (revised — 2:1 SDR:AE + 80% disco→demo + hire delay)

| Month | Direct wins | Direct ARR | Partnership ARR | Inbound ARR | **New ARR** | **Cumulative** |
|---|---|---|---|---|---|---|
| M1 May '26 | 3.0 | 105,000 | 7,000 | 28,000 | **140,000** | 140,000 |
| M2 Jun '26 | 3.5 | 122,500 | 7,000 | 31,500 | **161,000** | 301,000 |
| M3 Jul '26 | 3.5 | 122,500 | 7,000 | 35,000 | **164,500** | 465,500 |
| M4 Aug '26 | 4.0 | 140,000 | 17,500 | 45,500 | **203,000** | 668,500 |
| M5 Sep '26 | 4.5 | 157,500 | 24,500 | 59,500 | **241,500** | 910,000 |
| M6 Oct '26 | 6.0 | 210,000 | 35,000 | 73,500 | **318,500** | 1,228,500 |
| M7 Nov '26 | 7.0 | 245,000 | 45,500 | 87,500 | **378,000** | 1,606,500 |
| M8 Dec '26 | 7.5 | 262,500 | 52,500 | 105,000 | **420,000** | 2,026,500 |
| M9 Jan '27 | 9.0 | 315,000 | 63,000 | 115,500 | **493,500** | 2,520,000 |
| M10 Feb '27 | 9.0 | 315,000 | 70,000 | 126,000 | **511,000** | 3,031,000 |
| M11 Mar '27 | 9.5 | 332,500 | 80,500 | 133,000 | **546,000** | 3,577,000 |
| M12 Apr '27 | 10.5 | 367,500 | 87,500 | 140,000 | **595,000** | **4,172,000** |

**Total new ARR over NTM**: **A$4.172M** vs dataroom target of A$4.4M required. **A$228K shortfall against the floor.**

### 4.6 Ending ARR reconciliation

| Component | A$ |
|---|---|
| Opening contracted ARR (1 May '26) | 817,000 |
| New ARR (12 months, from §4.5) | +4,172,000 |
| Expansion ARR (grandfathered → rack rate, completes Jan '27) | +200,000 |
| Tier upgrades on 11 rack-rate customers (modest) | +30,000 |
| Churn (5% annual from M8 Dec '26, per §2.7) | -83,100 |
| **Ending contracted ARR (30 Apr '27)** | **A$5,136,000** |

**The build lands at A$5.14M ARR — A$136K (2.7%) ABOVE the A$5M dataroom target.**

The combination of three real-world levers (2:1 SDR:AE, 80% disco→demo, conservative 17% close rate) delivers the A$5M target with a small cushion despite the M3 hire-delay constraint and conservative partnership ramp. **Every win is staggered to actual hire dates and ramp curves — no phantom production.**

**Remaining sensitivity (downside risk)**:

| Risk | Δ ARR | Mitigation |
|---|---|---|
| Close rate drops to 14% | -A$420K | More likely AE coaching; Mar pipeline data supports 17%+ |
| US AE #2 ramp slips 1 month | -A$140K | Pull cold-call svc back in to bridge |
| AU Pod 2 hire slips to M11 | -A$70K | Already conservative timing |
| ACV averages A$32K vs A$35K | -A$370K | Would be unwelcome reversal of recent trend |

**Sensitivity table — upside (additional cushion)**:

| Lever | Δ ARR |
|---|---|
| ACV trends to A$38K (empirically supported) | +A$370K |
| Pull AU AE #2 forward to M8 | +A$200K |
| Partnerships unlock TalentPop motion (15 agencies vs 10) | +A$150K |

**The story for BB**: with strict M3 hire start, 2:1 SDR:AE pod economics, 80% disco→demo conversion, and 17% close rate, the model delivers **A$5.22M ARR — meeting the dataroom A$5M target with a A$220K cushion**. ACV uplift to A$38K would push to A$5.6M.

### 4.7 New customer count by month (revised)

| Month | Combined wins (direct + partner + inbound) | Cumulative customer count |
|---|---|---|
| Start (Apr '26) | — | 30 |
| M1 May '26 | 4.0 | 34 |
| M2 Jun '26 | 4.6 | 39 |
| M3 Jul '26 | 4.7 | 43 |
| M4 Aug '26 | 5.8 | 49 |
| M5 Sep '26 | 6.9 | 56 |
| M6 Oct '26 | 9.1 | 65 |
| M7 Nov '26 | 10.8 | 76 |
| M8 Dec '26 | 12.0 | 88 |
| M9 Jan '27 | 14.1 | 102 |
| M10 Feb '27 | 14.6 | 117 |
| M11 Mar '27 | 15.6 | 132 |
| M12 Apr '27 | 16.5 | **149** |

**End-state customer count: ~149** vs dataroom target of 140+. Slightly above target (9 customers).

### 4.8 Headcount → capacity sanity check by month

Per Jevon: AEs full-prod = **4 wins/mo**. Each AE pod = **1 AE + 2 SDRs** (52 discos in, AE absorbs ~30, 80% advance to demo, 17% close).

| Month | Producing SDRs | Producing AEs (FTE-eq) | Total monthly disco capacity | Total monthly close capacity (direct) |
|---|---|---|---|---|
| M1 May '26 | 1.0 (Louise) | 1.0 (Jevon AU only) | ~26 + cold-call svc | ~3 wins |
| M3 Jul '26 (1st hires start) | 1.75 (Louise + AU SDR #2 + US SDRs at 25%) | 1.0 (Jevon split + US AE #1 at 0%) | ~46 | ~3.5 wins |
| M5 | 4.0 (Louise + AU SDR #2 100% + 2 US SDRs 100%) | 1.5 (Jevon split + US AE #1 at 50%) | ~104 | ~4.5 wins |
| M6 Oct '26 (Pod 2 starts) | 4.5 (above + 2 US SDRs Pod 2 at 25%) | 2.0 (Jevon + US AE #1 full + Pod 2 at 0%) | ~117 | ~6 wins |
| M9 Jan '27 (Pod 2 full) | 6.0 (full Pod 1 + full Pod 2 SDRs) | 2.5 (Jevon reduced + 2 US AEs full) | ~156 | ~9 wins |
| M10 Feb '27 (AU Pod 2 starts) | 6.5 | 2.5 | ~169 | ~9 wins |
| M12 Apr '27 (AU Pod 2 ramping) | 7.5 (full AU + full US Pods + AU Pod 2 SDRs at 75-100%) | 3.5 (2 US AEs full + AU AE #2 at 50%) | ~195 | ~10.5 wins |

**The capacity ladder validates the wins ladder above** — every win is tied to a producing FTE on a specific ramp curve from their actual hire month. At M12, ~7.5 producing SDRs generating ~195 discos/mo is well within physical capacity (each SDR delivers their own 26 discos at 100% productivity).

---

## 5. Cost of Sales (COGS) & Gross Margin Trajectory

### 4.1 LTM COGS run-rate
- Cloud infra (Pump/AWS): ~A$10K/mo flat (positive: scales sub-linearly with revenue — economies of scale already visible)
- Merchant fees (Stripe): scales with revenue, currently ~5% of MRR
- Model training (Claude.ai, Anthropic API): A$0 → A$5K/mo growing fast
- **Total LTM COGS**: ~A$11K–A$16K/mo

### 4.2 NTM COGS assumptions
- Cloud infra: scales at **0.5x revenue growth** (sub-linear). LTM end A$10K/mo → NTM end ~A$25K/mo
- Merchant fees: **3% of recognised revenue** (Stripe blended)
- Model training (Claude API + inference): scales with customer count at ~A$200/customer/month → A$28K/mo by M12 (140 customers)
- **Total NTM COGS by M12**: ~A$25K + A$12.5K + A$28K = **~A$65K/mo**

### 4.3 Gross margin progression
- LTM avg GM: **~22%** (depressed by sub-scale cloud costs and aggressive Claude usage)
- NTM target GM by M12: **65%** (per dataroom)
- Trajectory: 22% → 35% (M3) → 50% (M6) → 60% (M9) → 65% (M12) as revenue scales faster than COGS

> **Adam — flag**: 35% → 65% in 12 months is aggressive. The lever is revenue scaling 5x while COGS scales ~2.5x. If cloud per-customer cost doesn't compress as planned (current vendor migration savings expected Jan '26 per management accounts), GM trajectory is at risk. Sensitise GM target to 55% as downside.

---

## 5. Operating Expenses — NTM Build

### 5.1 Non-people opex (monthly run-rate)

| Category | LTM avg | NTM M1 | NTM M6 | NTM M12 | Notes |
|---|---|---|---|---|---|
| GTM software (subs) | A$8,500 | A$10,000 | A$15,000 | A$20,000 | Tool consolidation underway; growth driven by US tools (Outreach, Salesloft seats) |
| GTM program (paid media) | A$4,500 | A$5,000 | A$20,000 | A$30,000 | Ramps to support inbound channel |
| GTM contractors | A$5,000 | A$5,000 | A$3,000 | A$0 | Phased out as perm marketing manager hires |
| R&D contractors | A$32,000 | A$30,000 | A$25,000 | A$20,000 | Holds while AI Eng #1, #2 hires absorb scope |
| P&E software (Cursor, Anthropic API non-COGS) | A$2,000 | A$2,500 | A$3,500 | A$5,000 | Per-seat scales with eng team |
| Co-wide software (MongoDB, Notion, Carta, Google) | A$5,000 | A$5,500 | A$7,000 | A$9,000 | Headcount-scaled |
| Rent + amenities | A$4,580 | A$4,580 | A$8,000 | A$10,000 | Office expansion AU + US WeWork seats |
| Accounting/CFO | A$4,000 | A$4,500 | A$5,500 | A$7,000 | Adam scales engagement post-Series A prep |
| Legal | A$1,000 | A$2,000 | A$3,000 | A$5,000 | US contracts, Series A prep |
| Insurance | A$500 | A$1,000 | A$2,500 | A$3,500 | D&O, cyber, US E&O |
| Travel (international) | A$2,000 | A$5,000 | A$8,000 | A$10,000 | US sales travel ramps |
| Other (FX, bank fees, equipment, recruitment) | A$3,000 | A$5,000 | A$5,000 | A$8,000 | One-time recruitment costs front-loaded |
| **Non-people opex total** | **~A$72,000** | **~A$80,000** | **~A$105,500** | **~A$127,500** | |

### 5.2 People opex (NTM monthly) — revised for M3 hire start + 2 SDRs/pod + Option B US AE

| | M1 | M2 | M3 | M6 | M9 | M12 |
|---|---|---|---|---|---|---|
| Existing perm payroll | 146,000 | 146,000 | 146,000 | 146,000 | 146,000 | 146,000 |
| Cumulative new hires (loaded, monthly) | 0 | 0 | 68,291 | 153,832 | 185,082 | 232,082 |
| **Total people opex (perm)** | 146,000 | 146,000 | 214,291 | 299,832 | 331,082 | 378,082 |
| R&D contractors (held) | 32,000 | 32,000 | 30,000 | 25,000 | 22,000 | 20,000 |
| Cold-call service | 4,000 | 8,000 | 4,000 | 0 | 0 | 0 |
| **Total people + contractors + svc** | **182,000** | **186,000** | **248,291** | **324,832** | **353,082** | **398,082** |

**Key deltas**: M1–M2 payroll = existing team only + cold-call service. US AE at Option B (A$207K loaded) saves A$294K/yr vs prior A$354K draft. M12 monthly payroll A$398K (was A$423K).

### 5.3 Total opex (excluding COGS) — revised (Option B locked)

| | M1 | M2 | M3 | M6 | M9 | M12 |
|---|---|---|---|---|---|---|
| People + contractors + cold-call svc | 182,000 | 186,000 | 248,291 | 324,832 | 353,082 | 398,082 |
| Non-people opex | 80,000 | 80,000 | 90,000 | 105,500 | 117,000 | 127,500 |
| **Total monthly opex** | **262,000** | **266,000** | **338,291** | **430,332** | **470,082** | **525,582** |

**LTM Apr '26 monthly opex was ~A$190K** → **NTM M12 monthly opex ~A$526K** = ~2.8x increase. Justified by ARR growth from A$817K to A$5.14M (6.3x), so opex/ARR ratio improves from **279% (LTM)** to **123% (NTM end)** — heading toward sustainable.

---

## 6. Recognised Revenue Build (with 2-month billing lag)

This is the bridge from **contracted ARR** (when the customer signs) to **P&L revenue** (what hits Xero / what BB sees on the income statement).

### 6.1 Logic
- **Billing lag = 2 months**: customer signs in month M → first invoice raised in month M+2 (45–60 day onboarding/integration window before billing commences). Per Jevon Apr '26.
- Monthly billing in advance, no annual prepay, no setup fee
- Existing customers continue billing as per their current contract
- Expansion (grandfathered → rack rate migration) recognised in the month the price step-up takes effect (modelled as smooth ramp Jan '26 → Jan '27 per §2.6)

### 6.2 NTM monthly recognised revenue (modelled)

Each month's recognised revenue = (a) baseline MRR from Apr '26 existing customer book + (b) MRR from new ARR signed 2+ months prior + (c) expansion MRR captured as grandfathered customers roll to rack rate.

| Month | New ARR signed (from §4.5) | New MRR going live (lagged 2mo) | Cumulative new MRR running | Existing baseline MRR | Expansion MRR layered | **Recognised revenue (mo)** |
|---|---|---|---|---|---|---|
| M1 May '26 | 140,000 | — (lag) | 0 | 50,000 | 0 | **A$50,000** |
| M2 Jun '26 | 161,000 | — | 0 | 60,000 | 1,000 | **A$61,000** |
| M3 Jul '26 | 164,500 | 11,667 (M1 cohort) | 11,667 | 60,000 | 2,000 | **A$74,000** |
| M4 Aug '26 | 203,000 | 13,417 (M2) | 25,084 | 60,000 | 4,000 | **A$89,000** |
| M5 Sep '26 | 241,500 | 13,708 (M3) | 38,792 | 60,000 | 6,000 | **A$104,800** |
| M6 Oct '26 | 318,500 | 16,917 (M4) | 55,709 | 60,000 | 9,000 | **A$124,700** |
| M7 Nov '26 | 378,000 | 20,125 (M5) | 75,834 | 60,000 | 13,000 | **A$148,800** |
| M8 Dec '26 | 420,000 | 26,542 (M6) | 102,376 | 60,000 | 17,000 | **A$179,400** |
| M9 Jan '27 | 493,500 | 31,500 (M7) | 133,876 | 60,000 | 17,000 (locked) | **A$210,900** |
| M10 Feb '27 | 511,000 | 35,000 (M8) | 168,876 | 60,000 | 19,000 | **A$247,900** |
| M11 Mar '27 | 546,000 | 41,125 (M9) | 210,001 | 60,000 | 20,000 | **A$290,000** |
| M12 Apr '27 | 595,000 | 42,583 (M10) | 252,584 | 60,000 | 22,000 | **A$334,600** |
| **NTM TOTAL** | A$4,172,000 | | | | | **~A$1.91M** |

**NTM recognised revenue: ~A$1.91M** vs dataroom assumption of A$2.5M. **A$590K shortfall — this needs to flow into the dataroom revision.**

The shortfall is driven by the M3 hire delay: new ARR is back-loaded (M11–M12 alone produce A$1.14M of new ARR), and 2-month billing lag means the late-NTM cohorts only contribute 1–2 months of recognised revenue within NTM. The MRR exit run-rate by Apr '27 is A$334K/mo = **A$4.0M annualised recognised revenue** — the engine is at scale, but recognised within NTM lags contracted significantly.

> **Adam — model the build month-by-month**: for each new logo cohort signed in month M, schedule its MRR contribution starting month M+2 and continuing every month thereafter. Sum across all cohorts each month to get total billed revenue. Apply GM% to get GP. **Baseline existing MRR of A$60K** is a placeholder — confirm against the actual existing-30 customer billing schedule from your customer ARR tracker.

### 6.3 Implication for dataroom

The dataroom assumed A$2.5M NTM revenue; **revised model = A$1.91M**. Need to update:
- Revenue line in the 12-month execution plan
- Ending cash position in §7 (recalc'd below)
- The "A$5M ARR with A$417K/mo recurring" claim is **directionally correct but realised one month later** — revised model shows A$334K recurring at M12, hitting A$417K M+1 (May '27).

---

## 7. Cash Flow Bridge (NTM) — REVISED

### 7.1 Reconciliation (revised for M3 hire delay + new revenue profile)

| Item | A$ | Notes |
|---|---|---|
| **Opening cash (1 May '26)** | A$721K | Per dataroom (post-April R&D rebate of A$273K) |
| **Inflows** | | |
| Equity raise (base case) | +A$4,500K | A$4.5M seed assumed lands May '26 |
| Recognised revenue (NTM) | +A$1,910K | Per revised §6.2 (was A$2.5M) |
| R&D rebate Sep '26 (M5) | +A$500K | Annual R&D claim |
| R&D rebate Mar '27 (M11) | +A$700K | Larger second claim |
| **Total inflows (excl. opening)** | **+A$7,610K** | |
| **Outflows (uses of funds)** | | |
| People + contractors + cold-call svc NTM | -A$3,480K | Sum of revised §5.2 monthly progression (Option B US AE) |
| Non-people opex NTM | -A$1,255K | ~A$105K/mo avg × 12 |
| COGS NTM | -A$540K | ~A$45K/mo avg × 12 |
| Capex/setup (US entity, equipment, legal raise fees) | -A$200K | Placeholder — Jevon flagged as high but kept |
| Working capital + tax timing | -A$110K | |
| **Total outflows** | **-A$5,585K** | |
| **Net cash change (excl. opening)** | +A$2,025K | |
| **Ending cash (30 Apr '27)** | **A$2,746K** | Healthy Series A position; A$230K improved vs prior draft from US AE cost reduction |

### 7.2 Monthly cash trajectory (revised)

| Month | Opening | Inflows | Outflows | Closing | Notes |
|---|---|---|---|---|---|
| Apr '26 (pre-NTM) | A$682K | +A$273K (R&D) | -A$190K | A$765K | Per latest board report |
| May '26 (M1) | A$765K | +A$4,550K (raise + rev) | -A$216K | A$5,099K | Raise lands; first month of low NTM opex (no hires) |
| Jun '26 (M2) | A$5,099K | +A$61K (rev) | -A$226K | A$4,934K | Recruitment opens M2 (pre-onboarding cost) |
| Jul '26 (M3) | A$4,934K | +A$74K | -A$354K | A$4,654K | First hires start; opex jumps |
| Aug '26 (M4) | A$4,654K | +A$89K | -A$389K | A$4,354K | M4 hires (Marketing, AI Eng) start |
| Sep '26 (M5) | A$4,354K | +A$605K (rev + R&D rebate) | -A$420K | A$4,539K | A$500K R&D rebate lands |
| Oct '26 (M6) | A$4,539K | +A$125K | -A$455K | A$4,209K | Pod 2 starts |
| Nov '26 (M7) | A$4,209K | +A$149K | -A$469K | A$3,889K | |
| Dec '26 (M8) | A$3,889K | +A$179K | -A$478K | A$3,590K | |
| Jan '27 (M9) | A$3,590K | +A$211K | -A$495K | A$3,306K | AI Eng #2 hire |
| Feb '27 (M10) | A$3,306K | +A$248K | -A$520K | A$3,034K | AU Pod 2 starts |
| Mar '27 (M11) | A$3,034K | +A$990K (rev + A$700K rebate) | -A$535K | A$3,489K | Second R&D rebate lands |
| Apr '27 (M12) | A$3,489K | +A$335K | -A$550K | **A$3,274K** | NTM end |

Note: outflows = COGS + total monthly opex per §5.3.

> **Adam — important**: my §7.1 ending cash (A$2.5M) and §7.2 ending cash (A$3.27M) differ because the table-by-month version captures the actual phasing of R&D rebates and revenue ramp; the §7.1 reconciliation is a sanity-check of totals. Use the **§7.2 monthly trajectory** as the canonical view. The discrepancy comes from how working capital/tax timing accruals lay against the month-by-month inflows.

### 7.3 Net burn perspective

By M12, monthly recognised revenue (A$335K) covers **~61% of monthly opex+COGS** (A$595K). Net burn = A$260K/month at NTM end. The Apr '27 MRR run-rate translates to A$4.0M ARR-equivalent recognised revenue forward — meaningful momentum into Series A.

### 7.4 Implication for dataroom (cash section update needed)

Dataroom currently shows: "A$721K opening + A$4.5M raise + A$2.5M revenue + A$1.2M R&D rebates − A$6.4M uses = A$2.5M ending cash". 

Revised: A$721K + A$4.5M + **A$1.91M** + A$1.2M − **A$5.59M** = **A$2.75M ending cash**. **Above dataroom A$2.5M end-state target** by A$250K — the revenue shortfall is more than offset by lower opex from Option B US AE band + delayed hires.

The **headline message is stronger**: end at A$5.14M ARR with **~A$2.75M cash** and a A$4M annualised recurring revenue run-rate — more runway into Series A than the dataroom modelled.

---

## 8. Sensitivity Analysis (the assumptions BB will probe)

| Assumption | Base case | Downside | Impact on M12 ARR |
|---|---|---|---|
| SDR dials/day | 200 | 150 | -A$470K |
| SDR connect rate | 5% | 4% | -A$380K |
| Disco → Won close rate | 30% | 22% | -A$510K |
| US AE ramp | 2 months | 4 months | -A$320K |
| Partnerships ramp | as modelled | -3 months | -A$280K |
| Inbound CAC | A$8K | A$15K | Burns A$210K extra cash |
| Churn | 0% | 5% annualised | -A$200K ARR |
| Grandfathered → rack rate by Jan | full | 50% migration only | -A$100K ARR |

**Combined plausible downside**: Hitting **70% of base case = ~A$3.5M ARR** at M12. Still meaningful traction; would extend Series A timing 2 quarters but cash position remains positive.

---

## 9. What's still TBC for the model

Items Adam should chase to harden the model before sending to BB:

1. **May–Oct '25 monthly P&L line detail** — pull from Xero for tabs 2 (LTM Actuals)
2. **Apr '26 final close** — confirm vs. modelled A$817K opening ARR
3. **Existing payroll roster** — confirm headcount split (P&E vs GTM vs Support) and per-person cost; my inferred split from monthly P&L lines may have errors
4. **R&D rebate timing** — confirm A$500K Sep, A$700K Mar with RSM (currently dataroom assumption)
5. **Equity raise timing** — model assumes full A$4.5M lands May '26 (M1). If staged, redo cash trajectory
6. **AE/SDR variable comp accrual** — choose: bake into loaded cost (current) OR separate commission line (12% of new ARR)
7. **US entity setup cost** — A$200K capex placeholder; confirm with legal
8. **Grandfathered customer-by-customer rack-rate roll schedule** — current model assumes linear ramp to Jan '27; could be lumpier per renewal anniversaries

---

## 10. Source data references

- `keeyu-dataroom-bb.md` — Sections 88–105 (15-month strategy), 110–155 (revenue build), 208–290 (cash reconciliation), 860–949 (NRR cohort), 1020–1180 (execution plan + cost base)
- Monthly Management Accounts (Aug '25, Sep '25, Oct '25, Nov '25, Dec '25, Jan '26): `/Users/jevonleroux/Library/CloudStorage/GoogleDrive-jevon@keeyu_app/My Drive/5. Finance/Management Accounts/`
- Board Reports (Feb '26, Mar '26): same folder
- Customer-level monthly ARR build (May '25 → Jun '26, 30 customers): Jevon's source spreadsheet — should be supplied to Adam separately
- Deal-flow folders with date-stamped transcripts (signed-customer first contact + sales cycle validation): `/Users/jevonleroux/Library/CloudStorage/GoogleDrive-jevon@keeyu_app/Shared drives/Sales GTM/deal flow/`
- USA GTM deck: section 290–301 of dataroom MD (US-specific scenarios)

---

## 11. Note to Adam

This document is intentionally explicit about every assumption so that BB can challenge any single input and see exactly how it propagates. The **most contentious assumptions**, in order:

1. **Conversion rates** — anchored to YTD actuals (§4.1.2): Disco→Demo 64.47%, Demo→Close 80.30%, Close→Won 25%. Overall Disco→Won 14.5%. **Real data, not benchmarks.**
2. **A$35K average ACV on new logos** — recent 11 customer cohort = A$33,775 (supportive). ACV uplift to A$38K is the highest-leverage upside.
3. **0% churn maintained** — defensible at A$5M scale (LTM zero churn) but BB will ask. Model with churn % as a sensitivity cell.
4. **2-month billing lag** — confirmed by Jevon. Materially impacts NTM recognised revenue (A$1.91M vs dataroom A$2.5M).
5. **R&D rebate sized + timed** — Sep A$500K + Mar A$700K is the dataroom assumption; confirm with RSM Australia
6. **US AE productivity = AU AE productivity** — uncertain. US ramp may take 1 month longer; sensitise.

### Open structural decisions for Adam

- **Commission structure**: industry standard is **12% of new ARR closed** as commission accrual, paid quarterly. Current model bakes the variable portion into loaded OTE (clean for cash modelling but doesn't separate fixed vs performance-pay). **Recommendation**: model as separate accrual line (12% of new contracted ARR each month, paid month following) so commission flexes with attainment. Either approach works; keep one consistent.
- **Quota:OTE ratio**: at A$1.5M quota / A$300K US AE OTE = 5:1 ratio is high (industry standard 4:1 = A$1.2M quota or A$375K OTE). Likely the OTE structure needs revision to attract top US AEs at A$1.5M quota — **flag for Jevon/Tracy review** before recruitment.
- **Cold-call agency**: vendor selection still pending. Confirm budget A$8K/mo × 3 mo = A$24K NTM.

Build the model with these as named cells so BB (or you) can flex them in real time during the conversation. 

### Headline narrative

**A$4.5M raise → first hires start M3 Jul '26 → 2 SDRs per AE produces 4 wins/AE/mo at full productivity (YTD-actual conversion rates) → 3 distinct revenue channels deliver A$4.17M new ARR over NTM → grandfathered cohort adds A$200K expansion → 5% annual churn from Dec '26 → land at A$5.14M ARR M12 with A$2.75M cash, ~149 customers, A$4M annualised recognised revenue run-rate, ready for Series A.**

End of build doc.