DeckMatch Financial Model

• Addresses "top of funnel firehose" - unstructured inbound (referred, cold, hunted) that overwhelms analysts/recruiters/procurement teams.
• API-first co-pilot: user inputs a thesis/criteria prompt; AI ingests pitch decks / CVs / RFP docs → outputs structured data, AI-generated memo, auto-updates CRM, sends AI-generated feedback.
• Integrates via RESTful API into existing CRM/workflow stack.
• OpenAI ChatGPT plugin approval secured.
• Four vertical use-cases on one shared AI backbone: Private Markets, HR & Staffing, Tenders & RFPs, Grant Making.

Total addressable market broken out by vertical:

• Investment Opportunities: $1b p.a. market; 25,000 private market GPs across VC, PE, RE, Infra with $10tr AuM.
• HR & Recruitment: $100b p.a. market; $760b industry turnover p.a..
• Procurement: $4b p.a. market.
• Public Sector / Grant Making: $5b p.a. market.
• Industrial Application (knowledge sharing): $10b p.a. market.
• Combined TAM: ~$120b p.a..

No SAM or SOM defined in deck. Market sizing methodology not disclosed - these appear to be software/tech-spend sub-segments, not total industry revenue.

• SaaS subscription. Self-service upgrade path from free (beta) to paid.
• Target ACV: north of $20k p.a. (self-service validation goal).
• Implied ACV for first ARR goal: $10k p.a. per customer (20 customers × $10k = $200k ARR) - note this is below the $20k validation target, suggesting tiered or early-adopter pricing.
• API-first / RESTful API integration; potential for usage-based or per-seat components not stated in deck.
• Freemium funnel: free tier → paid upgrade; retention target of 30% for free users.
• Go-to-market: product-led growth (PLG), word-of-mouth beta, referral engine planned for 2024.

All figures are forward-looking targets / in-beta at time of deck - no revenue yet.

No live revenue, no churn data, no paid customer count in deck.

Moat framed as data and network effects:

• Unique dataset: aggregated top-of-funnel data across all clients → analytics on missed opportunities, diversity/ESG metrics, channel performance.
• Network effects: referral and onboarding quality improves as more opportunities flow through the platform; "stronger inbound from DeckMatch."
• Curated hunting ground: proprietary deal/candidate sourcing layer.
• No direct competitors named in deck.

Team:

• Leo Gasteen - Co-Founder, CEO. Previously founded Edgefolio (marketplace tech, asset management).
• Walid Mustapha, PhD - Co-Founder, CTO. Previously founded Homefair. Domain expertise: AI, LLMs, mathematical optimisation, marketplaces.

Funding ask:

• Round: Pre-Seed
• Amount: EUR 1m

Archetype + why: SaaS ARR model with a PLG (product-led growth) funnel layer. Revenue is subscription-based (annual contracts implied), with a freemium-to-paid conversion funnel. The horizontal expansion roadmap (4 verticals) warrants a segment/cohort layer, but Private Markets is the clear wedge - model that first and add expansion revenue as a separate line from Year 2.

Forecast horizon & granularity:

• Monthly for Year 1 (beta → first revenue, conversion rates matter); quarterly for Years 2–3.
• Total horizon: 3 years.

Key drivers & assumptions:

*Funnel / acquisition:*

• Beta users at close of beta (Q3): 100 - then model organic + referral growth post-beta.
• Monthly new free signups post-beta: 30–50/month, ramping; PLG/word-of-mouth only in Year 1, paid acquisition from Year 2.
• Free-to-paid conversion rate: 5–10%; industry PLG benchmark ~3–8% for B2B tools. Deck targets self-service upgrade but no rate stated.
• Free user monthly retention (engagement proxy): 30% target; used as activation/stickiness gate for conversion model.

*Pricing:*

• Entry ACV: $10k p.a. (implied from $200k ARR / 20 customers goal).
• Target ACV: >$20k p.a. (validation goal).
• Model two tiers: Starter ~$10k and Pro ~$20k+. Starter-to-Pro upsell rate ~20% in Year 2.
• Annual contracts, paid upfront or monthly - assume monthly billing for simplicity; no payment terms in deck.

*Churn:*

• Monthly gross churn: 2% (= ~22% annual) for Year 1 (early product); improves to 1.5%/month in Year 2 as product matures. No churn data in deck.

*Expansion / verticals:*

• Private Markets: wedge vertical, modelled from Q4 of Year 1.
• HR & Staffing: expansion from 2024; model as new revenue cohort from Year 2.
• Tenders & RFPs, Grant Making: Year 3 placeholder.
• Each new vertical adds 20–30% incremental ARR to prior year's base at launch.

*Cost structure:*

• Two founders; assume seed hire plan funded by EUR 1m raise: 2–3 engineering hires + 1 sales/CS hire in Year 1.
• Gross margin: 75–80% (API/compute costs for LLM inference are the primary COGS; typical for AI-SaaS at this scale).
• COGS per customer: ~$500–$1,000/year in LLM API costs at current pricing; will compress as volume grows.
• Opex: personnel-heavy in Year 1; add sales/marketing budget from Year 2 as PLG engine is validated.

*Capital:*

• EUR 1m pre-seed raise.
• EUR/USD rate: 1.08 (model in USD for comparability; flag in assumptions tab).
• Runway: 18 months from close of round, targeting $200k ARR before next raise.

Scenarios (Base / Bull / Bear):

• Flex variables: free-to-paid conversion rate, ACV (entry vs. target), monthly churn, new signup growth rate, vertical expansion timing.
• Base: 5% free-to-paid conversion, $10k ACV, 2% monthly churn.
• Bull: 8% conversion, $15k blended ACV (faster Pro tier uptake), 1.5% churn, HR vertical live in Q2 Year 2.
• Bear: 3% conversion, $8k ACV (discounting to close), 3% monthly churn, HR vertical pushed to Year 3.

Required sheets / outputs:

1. Assumptions - all drivers in one place, colour-coded vs..
2. Funnel - free signups → activated → converted to paid → churned (monthly waterfall).
3. ARR Bridge - new ARR, expansion ARR, churned ARR, net new ARR by month/quarter.
4. P&L - Revenue, COGS (LLM/infra), Gross Profit, Opex (Headcount, S&M, G&A), EBITDA, Net Loss.
5. Headcount - role-by-role hiring plan tied to funding runway.
6. Cash & Runway - starting cash (EUR 1m), monthly burn, runway to zero, next raise trigger.
7. Scenario toggle - Base / Bull / Bear via dropdown or named ranges.
8. Dashboard - KPIs: ARR, MRR, paying customers, blended ACV, gross margin %, runway (months).