Nokod Security Financial Model

• Product: "Nokod LCNC Analyzer" scans low-code / no-code apps across enterprise platforms (Microsoft Power Apps, Salesforce, ServiceNow, OutSystems); outputs alerts via "Nokod Appsec Portal" to security teams / SOC.
• Three detection pillars:

1. Vulnerable apps detection
2. Malicious apps detection
3. Non-compliant apps detection

• Architecture: Nokod appsec engine(s) → appsec model → data lake (apps + platform logs); research layer feeds the model.
• Value prop: Fills the security gap created by citizen-developer proliferation - existing appsec processes do not cover LCNC apps, and no adequate tooling exists (self-described blue ocean).

• TAM - top-down approach #1 (Appsec market):
• AlliedMarketResearch: $5.97B (2020), 18.7% CAGR → $33.9B by 2030.
• ResearchAndMarkets: $7.35B (2022), 18.5% CAGR → $33B by 2030.
• Deck conclusion: average $9.35B at 2023 × 65% LCNC share (Gartner) = $6.07B TAM at 2023.
• TAM - top-down approach #2 (LCNC platform market):
• Gartner (Dec 2022): $26.9B in 2023, 19.6% CAGR.
• Acumen: $16B in 2021, 28.8% CAGR → $159B by 2030.
• Deck conclusion: average $26.72B at 2023 × 15% security = $4B TAM at 2023.
• TAM - bottom-up approach:
• 350,000 large companies (250+ employees) worldwide (2021 figure).
• 20% assumed to use LCNC.
• Average annual deal size:.
• TAM at 2023:.
• Market context: Gartner projects 65% of all apps will be low-code by 2024.

• Business model: Subscription, correlated with number of protected apps.
• Pricing unit: Per-app (i.e., usage-/volume-based subscription). Exact price per app not disclosed.
• Channels: Direct sales initially.
• Buyer: CISO, Director of Appsec.
• Entry point (champion): Digital transformation manager / Digital channel manager.
• Target customer: Mid-market and upward enterprises using LCNC tools with a dedicated appsec team.
• Covered platforms at MVP: Microsoft Power Apps, Salesforce, ServiceNow, OutSystems.

• Customer count:.
• ARR:.
• Product stage at Month 1: MVP, 1–2 covered platforms, design partner-ready.
• Validation: Meetings held with CISOs and Digital Managers; qualitative quotes confirm willingness to buy but no signed customers or ARR cited.
• Notable quote: "The solution makes a lot of sense. As soon as a security incident caused by a low code app is public, everyone would like to buy it" (CISO, public Insurtech).

• Self-described blue ocean: no direct LCNC-security specialist competitors named (competitor analysis redacted as strategic confidential).
• Competitive matrix shows Nokod in the upper-right quadrant vs. unnamed competitors.
• Moat arguments (implied): first-mover in dedicated LCNC appsec; deep LCNC-platform integration expertise; research layer / proprietary data lake; founding team pedigree (Imperva, Ping Identity).
• Indirect competitive pressure from: general appsec tools (SAST/DAST), LCNC platform vendors adding native security, enterprise security suites.

• Yair Finzi - Co-founder & CEO. 15 yrs cybersecurity; prev. founder & CEO of SecuredTouch (acq. by Ping Identity).
• Amichai Shulman - Co-founder & CTO. 25 yrs; prev. founder & CTO of Imperva (acq. by Thoma Bravo).
• Yuval Peled - VP Engineering. Backend/cloud; prev. Engineering Group Lead at Ping Identity.
• Funding ask: Seed round of $8M.
• Use of funds: Not explicitly stated. Timeline implies headcount growth from 4 FTEs (Month 1) → 15 FTEs (Month 13) → 25 FTEs (Month 24) and Series A preparation.

• Archetype + why: SaaS ARR model (per-app subscription). Revenue is explicitly subscription-based and correlated with number of protected apps - this is a classic seat/unit ARR build. Direct enterprise sales, mid-market upward, with annual contracts expected.

• Forecast horizon & granularity: 3 years (2023–2025, aligning with deck timeline), monthly for Years 1–2, quarterly for Year 3. Captures Seed → Series A gate.

• Key drivers & assumptions:

| Driver | Value | | -- | -- | | Addressable large enterprises | 350,000 (250+ employees) | | % using LCNC | 20% = 70,000 prospective accounts | | Initial geography focus | North America + EMEA | | Target segment | Mid-market upward (direct sales) | | Sales motion | Direct sales (outbound, CISO-led) | | Company headcount Month 1 / 13 / 24 | 4 / 15 / 25 FTEs | | Seed raise | $8M | | New logos per month (Yr 1) | 1–2 design partners → ramp to paid | | Average Contract Value (ACV) | $50K–$150K/yr | | Apps per customer | 20–100 apps | | Price per protected app per year | $500–$2,000 | | Gross margin | 75–85% | | Sales cycle | 3–6 months | | Annual churn (logo) | 5–10% | | Expansion / upsell rate | 10–20% NRR uplift | | Burn / OpEx | Model from headcount plan: 4 → 15 → 25 FTEs | | Average fully-loaded cost per FTE | $150K–$200K/yr (Israel + US blended) | | Series A raise trigger | Month ~24, ARR milestone |

• Scenarios (Base / Bull / Bear - which variables flex):
• Base: 2 new logos/month by Month 6, ACV $80K, 80% gross margin, churn 7%.
• Bull: 3–4 logos/month, ACV $120K (more apps per account), low churn 4%, faster platform expansion.
• Bear: 1 logo/month, longer sales cycles (6–9 months), ACV $50K (smaller deals), churn 10%; tests runway to Series A.

• Required sheets / outputs:

1. Assumptions - all drivers on one sheet, toggleable for scenarios.
2. Revenue build - new logos × ACV + expansion ARR; monthly new ARR, churn, net new ARR, ending ARR.
3. P&L - Revenue, COGS (hosting, support), Gross Profit, OpEx (R&D, S&M, G&A), EBITDA, Net Income.
4. Headcount plan - role-level FTE schedule tied to hiring plan (4 → 15 → 25).
5. Cash / Runway - Seed $8M less monthly burn; flag runway to Series A gate.
6. KPI dashboard - ARR, MRR, logo count, ACV, NRR, burn rate, runway months.