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Coralogix Financial Model

Crypto/Web3 Startup Financials (Free Excel Download)

Cloud-native observability platform (logs, metrics, security) using patented stateful streaming analytics to decouple indexing from real-time analysis, delivering up to 70% storage savings vs. legacy tools.

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About this model

Coralogix is a cloud-native observability platform for logs, metrics, and security analytics. Its stateful streaming architecture separates real-time analysis from conventional indexing, which the company says can reduce storage costs by up to 70% compared with legacy observability tools.

The company sells globally to enterprises and had raised more than $40 million when the deck was prepared. Its compliance posture spans ISO, GDPR, and PCI, while the product’s core economic tension is clear: customers want growing data ingestion and broad retention, but the provider must control the cloud cost of processing that data.

Forecast enterprise logos, initial contract value, data ingestion, expansion, renewals, and churn to build ARR and usage revenue. Derive COGS from ingestion and storage economics instead of applying a generic margin, then include implementation and customer-success capacity. Scenarios should flex net retention, usage growth, pricing, and cloud efficiency, which jointly determine the benefit of the streaming architecture.

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 Coralogix

coralogix.com
Read the pitch deck
Coralogix pitch deck cover
View on makeslides.com
Total raised
$55.0M
Funding round
Series C
Founded
2021
Category
Crypto/Web3
Customer
B2B
Geography
Global

How to build a detailed financial model for Coralogix

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

Product & value proposition

  • Patented "Streama" technology: analyze logs/metrics in real time before indexing; skip indexing for low-priority data
  • Three pillars: Log Analysis, Metrics, Cloud Security
  • Key differentiators vs. Splunk/SumoLogic/Elastic:
  • No storage/indexing required for real-time analytics - reduces storage costs up to 70%
  • No data loss, no throttling, no overages
  • OS-standard syntax (no proprietary query language) - removes vendor lock-in
  • ML-powered anomaly detection and dynamic alerting without static thresholds
  • Pricing model: pay per GB ingested - usage-based, not per-seat
  • Data platform angle (roadmap): targeting a broader "cloud data platform for any data, any syntax, any storage" by 2023
  • 100+ integrations; pluggable API for any new integration in under 24 hours

Revenue model

  • Pricing unit: GB ingested per month - consumption/usage-based
  • Tiers implied by "TCO Data Orchestration" feature: customers can route data to hot index, archive, or analyze-without-index (three tiers of data treatment), which implies tiered pricing by data pipeline/storage tier. Explicit tier pricing not shown.
  • Sales motion: implied enterprise/mid-market B2B (Fortune 100 customers, Masterclass, Payoneer, Fiverr, Lufthansa, Adobe); no self-serve PLG motion explicitly described.
  • Channel: direct sales inferred; marketplace/reseller not mentioned.

Traction & metrics

  • 2,000+ paying customers
  • 10 Fortune 100 customers
  • $40M+ raised (cumulative)
  • 3M+ events processed per second
  • 500K+ apps monitored
  • 9.8/10 G2 Crowd rating
  • 3 patents for "Streama" technology
  • Founded 2015
  • No ARR or revenue figures disclosed.

Case study - monday.com:

  • monday.com annual revenue at time of case study: $130M
  • 10x log volume growth at monday.com
  • 60% reduced MTTR after Coralogix
  • $100K saved/year by monday.com using Coralogix

Unit economics

  • Only indirect signal: "up to 70% storage savings" for customers; "pay per GB ingested". No Coralogix-side margin data in deck.

Competition / moat

Named competitors (positioned as legacy):

  • Splunk (ingest/search/visualize, 2003)
  • SumoLogic ("Splunk in the cloud," 2010)
  • Elastic (multi-tenant search engine, 2010)
  • LogLogic (2002)

Moat claims:

  • 3 patents on "Streama" stateful streaming technology - structural differentiation
  • First-mover on decouple-index-from-analysis architecture
  • Network effects not claimed; stickiness via integrations (100+), CI/CD workflow embedding, and data already flowing through platform
  • OS-standard syntax (Lucene/PromQL) lowers switching-in cost vs. Splunk SPL

Team & funding ask / use of funds

Team:

  • Ariel Assaraf, CEO - veteran of Israeli intelligence unit 8200; former GL at Verint
  • Matt Handler, COO & President - former leader at Sumo Logic, NTT, Whitehat, LogLogic, HP
  • Yoni Farin, CTO - former engineering leader at Verint and Motorola

Funding:

  • $40M+ raised to date

Recommended financial model

Archetype + why: Usage-based SaaS (GB-ingested model) with a subscription revenue layer - sometimes called a "consumption ARR" model. Revenue is driven by data volume per customer, not seat count. The right archetype is a usage-based B2B SaaS model with:

  • Customer count × average GB/month/customer × price per GB = revenue
  • Layered by data tier (hot-indexed, archive, analyze-only) to capture the TCO optimization upsell/downsell dynamic

Forecast horizon & granularity:

  • 3 years monthly (Year 1–2 monthly, Year 3 quarterly is acceptable)
  • Monthly is required because usage-based businesses have visible seasonality and expansion/contraction revenue within cohorts

Key drivers & assumptions:

DriverValue / Tag
Starting customer count2,000
New customer adds / month~50–80/mo, implying ~600–960/yr net new; growth stage company
Average GB ingested / customer / month1–5 TB/month (log-heavy enterprise; varies widely by industry)
Price per GB ingested$0.15–$0.40/GB based on observable DevOps SaaS market comps (Datadog, Sumo)
Net revenue retention (NRR)120–130%; usage-based SaaS with data volume growth tends to expand revenue within cohort; monday.com 10x log volume growth is directional support
Gross logo churn rate8–12% annually; B2B SaaS mid-market baseline
Gross margin65–75%; cloud-hosted SaaS with significant AWS/Kafka infrastructure costs; usage-based models often run 60–70% GM at scale
Sales & marketing as % of revenue40–55%; growth-stage enterprise SaaS typical range
R&D as % of revenue20–30%; platform-heavy company with patented tech
G&A as % of revenue10–15%
Data tiers mix (hot / archive / analyze-only)40% / 30% / 30% blended; directly impacts COGS (storage costs)
Fortune 100 customer count10; higher ACV per enterprise customer - model separately if possible

Scenarios (Base / Bull / Bear - which variables flex):

  • Base: 50 new logos/month, NRR 120%, GM 70%, GB/customer growing 15% YoY
  • Bull: 80 new logos/month, NRR 130%, GM 72%, GB/customer growing 25% YoY (cloud workload explosion)
  • Bear: 30 new logos/month, NRR 108%, GM 65%, GB/customer flat (customers limit ingestion for cost control)

Required sheets / outputs:

  1. Assumptions - all drivers centralized, tagged or
  2. Customer cohort model - monthly new customer adds, churn, expansion by cohort; outputs ending customers and cohort ARR
  3. Revenue build - consumption revenue (GB × price) + any base subscription fee; split by data tier (hot/archive/analyze)
  4. P&L (Income Statement) - Revenue → Gross Profit → OpEx (S&M, R&D, G&A) → EBITDA → Net Loss
  5. Cash & runway - starting cash (infer from $40M+ raised minus burn), monthly cash burn, months of runway
  6. KPI dashboard - ARR, NRR, Gross Margin %, CAC payback (once assumptions populated), logo count, GB processed

Frequently asked

Is the Coralogix financial model free?+

Yes. The Coralogix 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 Coralogix'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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