# Ably Financial Model

Enterprise realtime messaging infrastructure (pub/sub) delivered as a cloud-native platform, enabling developers to build scalable live experiences without managing complex realtime infrastructure.

- Canonical: https://finamodel.com/startups/ably
- Excel download: https://finamodel.com/startup-models/ably.xlsx
- Category: Dev Tools
- Model type: SaaS ARR / Valuation
- Funding round: Series B
- Funding: $70M
- Founded: 2021
- Geography: Global (data centres cited in USA East Coast and Germany [DECK, slide 15]).
- Customer: B2B

## About the company

Ably provides cloud-native realtime messaging infrastructure for developers building live, synchronized experiences. Its pub/sub platform supports multiple protocols and handles ordering, presence, history, recovery, and reliable delivery without teams operating their own realtime stack.

The commercial model follows developer-infrastructure patterns: a free entry point, tiered plans, and enterprise contracts priced around consumption such as messages, connections, and data transfer. Enterprise buyers can add service levels, compliance, and dedicated deployment needs.

The model is usage-based SaaS. Developer adoption, active applications, messages, concurrent connections, data usage, and price per unit build revenue, with enterprise contracts modeled separately. Free-to-paid conversion, usage expansion, infrastructure cost, reliability investment, and sales efficiency determine gross margin and ARR growth.

## What's included

- 5-year monthly revenue build with stage-appropriate growth assumptions
- Full P&L, headcount plan, and operating-expense schedule
- Cash-flow statement, runway, and burn-rate tracking
- Valuation via exit multiple with a DCF cross-check
- Returns analysis with MOIC and IRR
- Unit economics including CAC, LTV, payback, and cohort retention

## Product & value proposition

- Cloud-native pub/sub messaging platform delivering realtime data synchronisation at the edge.
- Four pillars: Predictable Performance, Integrity of Data, High Scalability of Service, Reliability of Infrastructure.
- Core capabilities: pub/sub channels, presence, guaranteed ordering, idempotent/exactly-once delivery, message delta compression, message history, stream resume.
- Multi-protocol: WebSockets, MQTT, SSE, HTTP, STOMP, AMQP, Pusher-compatible, PubNub-compatible.
- Integrations: Zapier, IFTTT, AWS Lambda, Azure Functions, Google Cloud Functions, Cloudflare Workers, AWS Kinesis, AWS SQS, RabbitMQ, Apache Pulsar.
- Push notifications: APNS, FCM, direct publishing.
- Free streaming data sources (Transport, Finance, News, Weather, Social media).
- Use cases: driver tracking on maps, IoT device communication, remote collaboration, internet-scale live events, business-critical chat.
- Value prop: accelerate time to market, remove UX/brand risk from realtime requirements, provide future-proof infrastructure.

## Market

- Directional market framing: "By 2025 it is estimated that 30% of all global data will be realtime data vs. the fraction it makes up today". No source cited.
- Vision framing: "Realtime experiences for a billion people each month" stated as next milestone.
- No TAM/SAM/SOM figures, no market-size dollar estimates, no named analyst reports in the deck.

## Revenue model

- Not explicitly stated in the deck.
- Usage-based + tiered subscription: standard for developer infrastructure / messaging platforms (Twilio, Pusher, PubNub model). Key consumption units likely: messages/month, peak concurrent connections, channels, data transfer (GB). Enterprise tier adds SLAs, dedicated clusters, compliance.
- Self-serve free tier → paid tiers → enterprise contracts. Developer-led growth motion implied by product positioning and protocol compatibility list.
- Revenue levers: message volume, connection count, number of apps/workspaces, add-ons (push notifications, queues, integrations).

## Traction & metrics

- Only aspirational metric: "a billion people each month" as a target/vision - not current traction.

## Competition / moat

- Competitors referenced implicitly via protocol compatibility (Pusher-compatible, PubNub-compatible APIs) - signals direct competition with Pusher and PubNub.
- Moat articulated as: the "four pillars of dependability" - particularly guaranteed ordering and exactly-once delivery (technically hard problems) plus edge-native distributed architecture.
- Vision differentiator: positioning toward the "decade of distribution" - local-first, edge-processed, distributed-sync use cases - implying a strategic move beyond simple pub/sub toward a broader realtime data fabric.
- No explicit competitive matrix or named competitor analysis in the deck.

## Team & funding ask / use of funds

- Presenter: Matthew O'Riordan (CEO/co-founder implied).
- No team slide, no org chart, no funding ask slide, no use-of-funds breakdown in the deck.
- This is a "business update & outlook" deck, not a fundraising pitch - consistent with absence of ask/terms.

## Recommended financial model

- **Archetype + why:** Usage-based SaaS / developer infrastructure revenue model. Ably sells API access priced on consumption (messages, connections, data) with tiered plans - the same commercial pattern as Twilio, Pusher, PubNub, Ably's direct comps. A pure ARR subscription model would misrepresent the variable-cost-driven revenue structure. The model should have a usage-volume engine feeding MRR/ARR alongside a cohort-based expansion/contraction layer.

- **Forecast horizon & granularity:** 3 years (2021–2023) monthly. Monthly granularity is essential to capture usage seasonality, cohort dynamics, and developer adoption curves. Year 3 can roll to quarterly for the board summary.

- **Key drivers & assumptions:**

| Driver | Value |
| -- | -- |
| Starting free-tier accounts | Unknown |
| Free-to-paid conversion rate | 3–6% |
| Monthly new paid account additions (start of period) | Unknown |
| MoM paid account growth rate | 8–12% |
| Average messages/month per paid account | 50M–500M |
| Average revenue per account (ARPA) / month | $200–$2,000 |
| Enterprise contract share of accounts | 10–20% |
| Enterprise ARPA / month | $5,000–$20,000 |
| Gross margin | 60–70% |
| Net Revenue Retention (NRR) | 110–125% |
| Monthly churn (paid accounts) | 1.5–3% |
| S&M as % of revenue | 25–35% |
| R&D as % of revenue | 30–40% |
| G&A as % of revenue | 10–15% |
| Headcount at model start | Unknown |
| Realtime data market growth rate | "30% of global data will be realtime by 2025" |

- **Scenarios (Base / Bull / Bear - which variables flex):**
  - **Base:** 10% MoM new paid account growth; 110% NRR; 2% logo churn; 65% gross margin.
  - **Bull:** 15% MoM new paid growth; 125% NRR (strong usage expansion); 1.5% churn; 70% gross margin (scale leverage on network costs).
  - **Bear:** 6% MoM new paid growth; 100% NRR (minimal expansion); 3% churn; 58% gross margin (infra costs don't compress).

- **Required sheets / outputs:**
  1. **Assumptions** - all drivers consolidated, tagged /, with scenario toggles.
  2. **Cohort Engine** - monthly cohort of new paid accounts; revenue per cohort by age; churn and expansion applied per cohort.
  3. **Revenue Build** - SMB/self-serve vs. enterprise split; usage tier breakdown; MRR bridge (new, expansion, contraction, churn).
  4. **P&L (Income Statement)** - Revenue → Gross Profit → EBITDA. OpEx by function (S&M, R&D, G&A). Operating loss / burn rate.
  5. **Headcount Plan** - by function, linked to revenue milestones; drives OpEx.
  6. **Cash & Runway** - starting cash balance (not in deck, requires input), monthly burn, runway to zero / to next milestone.
  7. **KPI Dashboard** - ARR, MRR, ARPA, Gross Margin %, NRR, logo churn, LTV/CAC (estimated), months of runway.

## Frequently asked questions

### Is the Ably financial model free?

Yes. The Ably model is a free Excel download with live formulas.

### Can I change the assumptions?

Yes. The workbook is editable and its live formulas recalculate when assumptions change.