M3

M30 Financial Model

• Single platform to explore, discover, and consume public APIs.
• One consolidated billing account with consumption-based pricing.
• Unified client framework: one set of docs, client libraries, and examples.
• Built as a serverless cloud abstraction over public cloud infrastructure.
• Powered by open-source "Micro" framework (micro/micro on GitHub).
• Product screens show: API marketplace catalog, per-API docs/sandbox, and a billing dashboard showing balance ($28.43 visible in UI) and usage chart.

• Context provided via the problem slide: the "Third-Party API Economy" is fragmented across 30+ named vendors across Payments, Payroll, E-Commerce, Messaging, Health, Search, CMS, Insurtech, Security, Identity, Logistics, Forms, Verification, Data Mgmt, Video, Automation, Location categories.

Three-layer model:

• Pay-as-you-grow overage: $1 per million API calls after free tier.
• Premium paid services on top (SMS, email, geocoding, news, etc.) - priced per-call above the base tier.
• Future recurring subscriptions (Pro/Team/Business starting at $20/month mentioned as forward-looking).
• Channel: self-serve / PLG (developer-led, free-to-start). No enterprise/sales channel mentioned.

From slide 5 (confirmed via image):

• 6,500 signups since launch
• 1 million API calls per month (current run-rate)
• 60 APIs on the platform
• 5 minutes to first API call (time-to-value)

From slide 5 chart image: Total API Requests line chart Jul–Feb; scale tops ~3.5M cumulative; curve inflects sharply Nov–Feb, reaching ~3.5M cumulative by Feb 1.

From slide 6 (Usage Data dashboard image):

• Signups chart (Jul–Feb): rises from ~0 to ~5,000 total, steeper inflection Oct–Nov.
• API Requests chart (Jul–Feb): multi-API stacked lines; top API (db) reaches ~1,500K cumulative by Feb; weather and cache also material.
• Users by API bar chart: top APIs by user count include db, weather, id, email, helloworld, currency - db is clearly #1, weather #2.

From slide 7 (Open Source):

• Underlying Micro framework: ~10,500 GitHub stars as of 2021 (chart reads ~10k+ by late 2021, from ~700 in 2017).
• Micro processes 1 billion requests per day.

No revenue figures disclosed.

• No CAC, LTV, or payback figures in deck.
• Implied gross margin is high (API pass-through with serverless infra); no cost data disclosed.
• Overage pricing: $1/M calls above free tier. At 1M calls/month run-rate, current monetizable volume is near zero (all on free tier).

• Problem framing: no current aggregator with standardised consumption model exists.
• Moat stated: open-source Micro framework with 10k+ GitHub stars and 1B requests/day scale provides credibility and OSS developer distribution.
• No explicit competitive comparison slide.
• Case study: OpenBooking (CEO Louis Brauer) migrated from Twilio SMS → M3O SMS, Sendgrid/Postmark → M3O Email, AWS S3 → M3O Space, citing ease of use, single billing, reduced complexity.

Team:

• Asim Aslam - CEO; background in Micro (OSS)
• Dominic Wong - CTO; ex-Monzo
• Martin Virando - Dev UX; ex-Cisco

Existing investors:

• Blossom Capital
• Lightspeed Venture Partners
• Angels: Ross Mason, Luke Kanies, Spencer Kimball

Ask: Raising $5M

Use of funds:

• Accelerate growth and adoption
• Hire engineers and developer evangelists
• Build API integrations and client libraries

Milestones post-raise:

• Grow team to 10
• Catalog of 100 public APIs
• 100,000 users on the platform

• Archetype + why: Usage-based SaaS with freemium funnel. Revenue has two streams: (1) subscription MRR (Pro @ $25/mo, Team @ $45/user/mo) and (2) consumption overage ($1/M calls). Classic PLG funnel: free signups → paid conversion → expansion via seat/usage growth. 3-statement not warranted at this stage; a driver-based ARR/MRR model with unit-level cohort tracking is appropriate.

• Forecast horizon & granularity: Monthly, 36 months (3 years). Year 1 = actuals/near-term, Years 2–3 = projection.

• Key drivers & assumptions:
• Monthly new signups: ~500–700/mo implied by 6,500 over ~10 months → model as growing 5–10% MoM post-raise as hiring/evangelism kicks in
• Free-to-paid conversion rate: 3–5% of active users convert to Pro/Team (typical PLG benchmark); not in deck
• Paid tier mix: 80% Pro, 20% Team (no data; Team requires collab which implies teams, less common at early stage)
• Average team size (Team tier): 3 users/team
• Monthly churn on paid: 3–5%/month (early-stage developer tools benchmark)
• API calls per paid user/month: 5–20M (Pro includes 20M; most users likely sub-20M early)
• Overage revenue: negligible in Year 1 (most usage on free/within-plan); models as % of paid cohort exceeding plan limits, starting ~10% by Year 2
• Premium API attach rate (SMS, email, geocoding): 15% of paid users purchase at least one premium API service; average $10/mo
• Gross margin: 70–80% (API pass-through costs are infra + third-party API costs; no data)
• Headcount: starts at 3, grows to 10 post-raise; mostly engineering + 2 dev evangelists
• Avg engineer salary: $120K/yr (UK/US blend given Monzo/Blossom pedigree)
• Infra cost per million API calls: $0.10–0.20 (serverless cloud; needs sensitivity)

• Scenarios (Base / Bull / Bear - which variables flex):
• Base: 5% MoM signup growth, 3% free-to-paid conversion, 3% monthly churn
• Bull: 10% MoM signup growth, 5% conversion, 2% churn - inflects to profitability in ~30 months
• Bear: 3% MoM signup growth, 2% conversion, 6% churn - extends runway, requires bridge

• Required sheets / outputs:

1. `Assumptions` - all drivers in one place, flagged vs
2. `Funnel` - monthly signups → MAU → paid users (cohort-based)
3. `Revenue` - MRR breakdown: Pro sub, Team sub, overage, premium APIs
4. `P&L` - gross profit, opex (headcount, infra, S&M), EBITDA, net burn
5. `Headcount` - role-by-role hiring plan tied to raise milestones
6. `Cash` - cash balance, monthly burn, runway from $5M raise
7. `Dashboard` - KPI summary: MRR, ARR, paid users, total signups, API call volume, burn, runway