ZEDCRIT TERMINAL

The First Multi-Paradigm Fusion Engine for 0DTE Options.

We fuse SEVEN mathematical paradigms — Kalman Innovation, GEX Analytics, Bayesian Inference, Institutional Flow, Machine Learning Calibration, Risk-Neutral Measures, and Extreme Value Theory — into a single 2D vector space. Think of it as a mathematical GPS for 0DTE options — it doesn't tell you where to go, it tells you the statistical probability of each path.

TARGET ROI: 1.3x – 8.9x
Raising
$300K
SAFE @ $6M Valuation Cap · 3 tranches
Unit Economics
5.4 : 1
LTV/CAC ratio (blended) · $4,283 LTV
Year 5 ARR
$2.61M
1,460 active clients · 27% EBITDA margin
Exit Projection
$10.4–15.6M
Base: $10.4–15.6M · Upside: $37.6–80M
💰 LTV/CAC 5.4:1 (blended) 📈 Break-even Year 2 🚀 Exit $10.4–15.6M
Platform Preview

Explore the Zedcrit Terminal interface. Swipe or scroll horizontally to see the dashboard, market forces, and regime detection in action.

Investor ROI Calculator

Model your return based on the SAFE terms. Exit valuations based on 10-15x EBITDA ($1.11M) yielding $11.1M–$16.7M in Year 5.

Investment Amount $100,000
Valuation Cap $6,000,000
Ownership5.00%
*Post-dilution logic applied (assuming 30% standard dilution)

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A

Executive Overview

A1. The Founder's Story

"I lost $25,000 in a single day. $15,000 on one account, $10,000 on another. I thought it was a choppy sideways day. I was wrong — the market had shifted into a strong downtrend. I averaged in. I held. The bounce never came."

— Adrian Danet, Founder & CEO

What I needed — but didn't have — was a system that could tell me in real time: the regime has shifted. This is no longer sideways. This is a downtrend. Exit now.

After that day I studied everything: Hidden Markov Models, Kalman filters, GEX analytics, market microstructure. The tools existed, but were scattered across expensive platforms, requiring PhD-level coding, and impossible to access in real time.

So I built my own. Zedcrit Terminal is the system I wish I had that day. It's the difference between gambling and making a statistically calculated decision. Adrian Oprisor joined as CTO, refined the engineering, and together we now have a functional prototype in Private Beta with 10 active traders.

A2. Executive Summary (One-Pager)

Investor Takeaway

3.6:1
LTV/CAC safety buffer
10/10
Retention after 30 days
$11.8K
Annual saving for user
*Takeaway Data: LTV/CAC ratio of 3.6:1 reflects our pessimistic $1,200 CAC vs $4,283 LTV (3.6:1 ratio). 10/10 retention is based on 10 Private Beta users remaining active after 60 days. $11.8K saving represents the typical capital a 0DTE options trader loses annually due to delayed data and theta decay without regime detection.
$300K
SAFE raise @ $6M cap — 3 milestone tranches of $100K each
5.4 : 1
LTV/CAC ratio — $4,283 blended LTV vs. ~$800 CAC
$2.61M
Year 5 ARR projection (1,460 active clients, factoring ~5.0% monthly churn)
~31% / >85%
Hardware margin / Software margin — Dual-model strategy enables premium upsell

The Problem in 1 Sentence

Active options traders lose thousands of dollars because they cannot identify market regimes in real time — and every available solution is either too expensive, too generic, not private, or technically inaccessible.

The Solution in 1 Sentence

Zedcrit Terminal is a plug-and-play hardware appliance that runs HMM regime detection, complete GEX analytics, and synthesized market forces locally on your desk — with $0/month data cost, using your existing Schwab account. Available in two configurations: Zedcrit Core ($799) and the premium Zedcrit Pro ($1,499).

CapabilityWhat It Does
HMM Regime DetectionClassifies market regime in real time: uptrend, downtrend, sideways, high volatility
GEX / DEX AnalyticsCall Wall, Put Wall, Gamma Flip, Liquidity Void, Vanna & Charm flows
Market ForcesSynthesized into a single, intuitive dashboard score
Statistical Implied VectorWhere the market is statistically biased to move, based on all forces
Kalman-Filtered Z-ScoresZero-lag adaptive smoothing — more accurate than rolling windows

5-Year Projections (Conservative)

MetricYear 1Year 2Year 3Year 4Year 5
Active Clients (End of Year)652135579901,460
Total Collected Revenue (Cash)$213,801$659K$1.70M$2.89M$4.15M
↳ Hardware Revenue$86,115$240K$606K$948K$1.28M
↳ Subscription Revenue (Collected)$116,220$381K$996K$1.77M$2.61M
ARR (Annual Run-Rate)$116K$381K$996K$1.77M$2.61M
EBITDA−$33,349$53,925$559,290$888,570$1,117,730
EBITDA Margin−16%8%33%31%27%
Note on Year 1: ARR represents the end-of-year annualized run-rate, not the cash collected in Year 1. Total collected revenue is $213,801. EBITDA of −$33K reflects full-year fixed costs against prorated hardware/subscription revenue. Cash-flow positive in Year 2.

Exit: $11.1–16.7M (10-15x multiple on EBITDA) · Investor ROI: ~1.3x–2.0x on $300K @ $6M cap

A3. Elevator Pitches

For Traders (45 sec)

"I lost $25,000 in a single day because I couldn't see that the market had shifted regime. From that pain, I built Zedcrit — a hardware appliance that tells you, in real time, whether you're in an uptrend, downtrend, sideways, or high volatility regime. It's plug-and-play, 100% private, and costs $0/month in data fees."

For Investors / VCs (60 sec)

"0DTE options now account for 50%+ of SPX volume. But every existing tool was built for 30-day options — they use lagging indicators, single-paradigm models, and fixed weights.

0DTE requires a fundamentally different approach. It requires multi-paradigm fusion in real-time.

Zedcrit Terminal fuses SEVEN mathematical paradigms: Kalman Innovation for zero-lag regime detection, GEX Analytics for dealer positioning, Bayesian Inference for probability surfaces, Institutional Flow for smart money detection, Machine Learning for optimal force weighting, Risk-Neutral Measures for volatility pricing, and Extreme Value Theory for tail risk estimation.

40 dimensional forces — directional, kinetic, and frictional — are synthesized into a single 2D vector space using Welford's Online Variance.

The result is a Statistical Implied Vector that mathematically reveals, in real time, where the market is statistically biased to move. No other system does this. Because no one else has built the mathematics."

A4. Company Snapshot
CompanyZedcrit
ProductZedcrit Terminal — Quant Intelligence Appliance
CategoryFintech / Quantitative Analytics / Hardware-Enabled SaaS
Founded2024
Legal StructureC-Corp (planned)
LocationUS-based (remote)
WebsiteZedcrit.com
Mission"Democratize institutional-grade quantitative intelligence — accessible, affordable, and private for every active trader."
B

The Problem

B1. The Core Problem

Retail options traders are at a structural disadvantage against institutional players. The single biggest cause of trading losses is not a bad strategy — it's misidentifying the market environment.

What You ThinkMarket RealityResult
"It's a choppy day"Strong downtrendSell premium → blown out
"It's a trend"Sideways rangeTrend-follow → get chopped
"It's a pullback"Regime shiftAverage in → losses compound
"Low volatility"High volatilityGet stopped out repeatedly

Institutional vs. Retail: The Quant Gap

Hedge Funds Use

✅ Hidden Markov Models
✅ Kalman Filters
✅ GEX Analytics
✅ Market Forces Synthesis
✅ Real-time regime classification
Retail Traders Use

❌ Moving averages (lagging)
❌ RSI (generic)
❌ MACD (delayed)
❌ Gut feeling (unreliable)
❌ No regime detection

The Pain: You're fighting with stone tools against opponents using laser-guided missiles.

B2. Market Validation

"I've been trading 0DTE for 4 years. I've tried everything — SpotGamma, Cboe, custom Python scripts. Nothing comes close to Zedcrit. The regime detection caught a reversal 17 minutes before my usual indicators. Saved me $8,000 in one day."

— Private Beta Trader #3, $420K account

We interviewed 15+ active options traders. Their responses validated the problem at scale:

85%
Confirmed lack of regime clarity directly affected their profitability
78%
Would pay for better real-time regime detection
53%
Have lost >$10K from a single misidentified regime
91%
Would switch to a $0 monthly data-cost solution

Trader Quotes

"I lost $12,000 because I thought it was a pullback. It was a regime shift. If I'd had a system telling me, I'd have been out."

"I pay $1,200/month for data and still feel like I'm flying blind."

"I'm a coder, and even I find it impossible to build a full GEX + regime detection system. The complexity is staggering."

B3. Competitive Landscape

No solution delivers the full combination of HMM Regime Detection + GEX + Market Forces + Privacy + $0 data cost in a plug-and-play form factor.

SpotGammaOptionMetricsCboe LiveVolSpiderRockORATSDIY PythonTradingViewZedcrit Terminal
HMM Regime DetectionPartialPossible✅ Yes
Complete GEX AnalyticsPartial✅ Yes✅ Yes✅ Yes✅ YesPossible✅ Yes
Market Forces✅ Yes
100% Private (Local)❌ Cloud❌ Cloud❌ Cloud❌ Cloud❌ Cloud✅ Local❌ Cloud✅ Yes
Live Data Cost$1,000+/mo$0 (EOD)$2,000+/mo$3,000+/mo$500+/mo$100+/mo$0–50/mo$0 (Schwab API)
Monthly Software Cost$1,000+$5,000+$3,000+$3,500+$1,000+$100+$0–50$149 (all-in)
Setup5 minMonthsDaysWeeksDaysMonths2 min30 seconds
Technical SkillLowHigh (Quant)MediumHigh (API)MediumVery HighLowNone
IP ProtectionN/AN/AN/AN/AN/AExposedN/A✅ TPM 2.0
C

The Solution

C1. Product Overview — What is Zedcrit Terminal?

Zedcrit Terminal is a purpose-built Mini PC hardware appliance that brings institutional-grade quantitative intelligence to your desk. It plugs into your Ethernet, runs completely locally, and becomes operational in under 5 minutes.

StepActionTime
1Unbox and connect power + Ethernet2 min
2Open browser → http://zedcrit.local30 sec
3Enter your Schwab API token60 sec
4Trade with quantitative clarityImmediately

Use Case: The 0DTE Trader's Morning

TimeTrader ActionZedcrit Terminal
9:30 AMOpens positionRegime detected: Sideways
10:15 AMPrice drops slightlyKalman Innovation detects "surprise"
10:16 AMTrader is alertedRegime Shift: Downtrend
10:17 AMExits positionMinimal loss vs. catastrophic loss
10:30 AMPrice drops 50 pointsTrader is in cash, protected
Result: A $500 manageable loss instead of a $25,000 account blow-up.

Market Forces Covered

CategoryForces
Order FlowCLV (Cumulative Close Location Value), Tick Velocity, Speculative Pressure
VolatilityGK Volatility, Relative Volume, Volatility Spring, IV Skew
GreeksNet GEX, Vanna, Charm, Speed, Color, Vomma
InstitutionalDirectional Delta, Breadth Gravity, Hedge Gravity, Arbitrage Force
Market StructureCall Wall, Put Wall, Gamma Flip, Liquidity Void, Expected Pin
MomentumAcceleration, Efficiency Ratio, Fractal Dimension, Overlap Ratio
RiskImplied Skewness, Risk Premium Index, Tail Loss Measure
C2. Technical Architecture — The Multi-Paradigm Moat

Zedcrit fuses 7 mathematical paradigms across 11 technical layers, creating a coherent engine that is mathematically inimitabile and physically secure.

40 Forces
Welford Variance
ML Calibration
2D Vector
Foundational InfrastructureLayer 1: Data Ingestion — Polars (1-min rolling OHLCV), DuckDB, Real-time Schwab WebSocket
Paradigm 1: Stochastic State EstimationLayer 2: Kalman Innovation — Zero-lag regime detection. Innovation = Actual - Predicted
Paradigm 2: Options Flow AnalyticsLayer 3: GEX Analytics — Call/Put Walls, Gamma Flip, Liquidity Voids, Vanna & Charm, Net GEX
Paradigm 3: Bayesian InferenceLayer 4: Probability SurfacesP(Regime | New Data) updated instantly from Kalman Innovation
Paradigm 4: Institutional FlowLayer 5: Smart Money Detection — ES Basis Arbitrage, Breadth Gravity, Directional Delta, Mag7 Pull
Paradigm 5 & 6: Risk-Neutral & Extreme ValueLayer 6: Risk-Neutral Measures — BKM implied variance, SVIX premium, Corridor VIX
Layer 7: Extreme Value Theory — GPD fitted to OTM puts for tail risk & crash probability
Paradigm 7: ML Calibration & SynthesisLayer 8: Welford Online Variance — Bounds ANY force into [-3, +3] Sigma with O(1) updates
Layer 9: ML Calibration — Exhaustive Search + AIC validation + Huber/ElasticNet to optimize weights
Output & VisualizationLayer 10: 2D Phase Space Vector — Synthesizes Directional (Y), Kinetic, and Frictional (X) forces into (dx, dy)
Hardware SecurityLayer 11: IP Protection — Nuitka compilation, TPM 2.0, LUKS encryption, Remote Kill-Switch
C3. The Hardware "Trojan Horse" — Our Unfair Advantage

We live in the era of "vibe coding." A developer can clone a UI overnight. They cannot clone Zedcrit.

ThreatHow Hardware Solves It
IP TheftAlgorithms locked in TPM 2.0. Physically and economically infeasible to extract.
Data CostsCloud SaaS for 1,500 users = $75K–$110K/month AWS + institutional data licensing. Our edge model = <$20/user. (Annual savings of $540K-$954K). Margin preserved.
PrivacyPortfolio, P&L, and trade data never leave the client's desk. Zero transmission.
LatencyZero cloud round-trip. All math at the edge. Sub-millisecond updates.
Perceived ValueA physical device on your desk commands premium pricing — the retail Bloomberg Terminal analogy.
Cloud economics at 1,500 users: 3,000–6,000 vCPUs · ~24TB RAM · ~75TB NVMe storage · 1,500 persistent WebSockets = $75K–$110K/month. Our edge model costs <$20/user/month in maintenance, preserving >90% software margins permanently.
C4. Innovation & IP Protection

We do not file patents — patents require public disclosure. Our algorithms are protected by a layered trade secret strategy:

AssetProtection MethodStatus
HMM Regime Detection AlgorithmTrade Secret + TPM 2.0 hardware encryptionProtected
Forces Synthesis EngineTrade Secret + TPM 2.0 hardware encryptionProtected
Kalman Filter ImplementationTrade Secret + TPM 2.0 hardware encryptionProtected
All Python Source CodeCopyright + Nuitka compilation (prevents decompilation)Protected
Brand / TrademarksTrademark registrationPlanned
C5. Legal & Regulatory Compliance

SEC / FINRA — Not Investment Advice

Our analytics are strictly impersonal. They do not consider the user's risk profile, portfolio size, or financial goals — the fundamental SEC threshold for "investment advice." Every output uses statistical terminology (e.g., "Statistical Implied Vector") rather than trade recommendations ("Buy," "Sell").

OPRA Data Distribution — BYOD Model

Zedcrit operates on a Bring Your Own Data (BYOD) model. The client connects their own personal retail API key. All calculations happen locally on their hardware. Zero transmission of derived data back to our servers. Legally equivalent to a complex Excel macro running on the client's own laptop.

Legal ElementOur Approach
Terminology"Statistical Implied Vector" · "Historical Probability Level" · Never "Predicted Target" or "Trade Signal"
User Control100% of buy/sell decisions are made independently by the user. The system provides analytics, not actions.
Data HandlingClient's API key on client's hardware. Zero trading data retention. Minimal metadata (email, billing) stored encrypted.
EULAExplicit language: analytical tool, not financial advisor.
C6. Product Roadmap
Phase 1 (2024–2025)
Private Beta & Validation
✓ Functional prototype · ✓ Schwab WebSocket integration · ✓ HMM Regime Detection · ✓ GEX Analytics · ✓ Forces Dashboard · ✓ 10 traders in Private Beta · Launch Zero Day Spartan Community Funnel · IBKR API integration (Beta)
CURRENT — Phase 2 (2026+)
Commercial Launch — 85 Units
Landing page + waitlist · Pre-order campaign · First 85 commercial units shipped · Influencer partnerships · EULA finalization · FCC/CE certification · Tradier API integration (Full data redundancy)
Phase 3 (2027–2028)
Growth & Broker Expansion
150 units/year · Volume hardware procurement · Additional broker integrations (Tastytrade, etc.) · Community building (Discord, newsletter) · Referral programs
Phase 4 (2028–2031)
Scale & Expansion
350+ units/year · Mobile companion app · API for developers · International expansion
C7. Why We Win — Our Unfair Advantages
7
Mathematical paradigms fused — no competitor has more than 2
40
Dimensional forces synthesized — competitors use 2-5
Zero
Lag — Kalman Innovation detects shifts INSTANTLY
$0
Monthly data cost — BYOD model beats $1,000+/mo competitors
TPM
Hardware-protected IP — you cannot clone the math
10
Active traders in Private Beta — 100% retention, 4.8/5 satisfaction
D

Market Opportunity

D1. TAM / SAM / SOM
MarketSizeDefinition
TAM$500M+Global market for options analytics, quantitative data, and institutional tools
SAM$150MActive Schwab/ThinkOrSwim options traders + existing GEX platform users (US focus)
SOM (5-year target)$3M+~1,460 active units — <1% of our SAM. Extremely conservative.
*Methodology Note: TAM ($500M) is a bottom-up calculation based on FINRA/Cboe reports estimating ~3.5M active options traders globally, applying an estimated 10% premium tool adoption rate at an average $1,400/yr spend. SAM ($150M) isolates the ~1M highly active US retail/prop traders using advanced platforms. SOM ($3M) represents capturing just ~0.2% of the SAM by Year 5.

Proof of Traction

MetricResult
Active Traders10 in Private Beta
Retention100% after 30 days
Equivalent MRR$2,400 (projected)
Satisfaction Score4.8/5
Product risk is eliminated: Traders are already using Zedcrit Terminal in live market conditions and actively relying on it for daily decision making.

Key Market Tailwinds

Metric202020242026 (est.)
Daily options volume20M contracts45M+60M+
Retail options traders (US)2M10M+15M+
0DTE volume as % of SPX20%50%+60%+

0DTE options now account for the majority of SPX volume. These instruments require real-time regime detection — lagging indicators are structurally useless. Zedcrit is built precisely for this.

D2. The Competitive Matrix
CapabilitySpotGammaCboeORATSBloombergZedcrit
Zero-Lag Detection✅ Kalman
GEX AnalyticsPartialPartial✅ Complete
Bayesian Inference
Institutional Flow
Risk-Neutral MeasuresPartial✅ BKM/SVIX
Extreme Value Theory✅ GPD
ML Calibration✅ ElasticNet
40-Force Synthesis
2D Phase Space
Hardware-Protected IP✅ TPM 2.0
0DTE-Specific

Why 0DTE Changes Everything

0DTE is not "just another option." It is a fundamentally different asset class that breaks traditional 30-day models. This is why our Multi-Paradigm approach is strictly necessary.

0DTE CharacteristicImplicationWhy Legacy Tools Fail
Extreme Time DecayOption loses 50% of value in 30 mins30-60 min lag = tool is completely useless
Rapid Gamma ExpansionDealers hedge aggressively intradayGEX must be updated by the second
Intraday VolatilityRegimes shift in minutesHMMs must be continuously re-trained
Liquidity VoidsPrices gap through thin liquidity zonesLinear models fail structurally

Macro Trends Favoring Zedcrit

TrendWhy It Benefits Zedcrit
0DTE Revolution50%+ of SPX volume — demands second-by-second regime detection. Lagging indicators fail. HMM wins.
Democratization of QuantRetail traders want institutional-quality tools at accessible prices. Willingness to pay is rising.
Cloud Privacy BacklashData breaches rising. Traders want local control of strategy, P&L, and positions. We are the answer.
Commission EliminationZero commissions → traders have more capital to invest in analytical tools and edge.
D3. Target Customer Profile

Primary: The Active Options Trader

AttributeProfile
Age30–55
Account Size$50,000 – $500,000
Trading FrequencyMultiple times per week (0DTE / weekly options)
Current Spend on Tools$500 – $2,000/month
Primary PainLosing money from misidentified market regimes
Technical SkillLow to medium
PlatformSchwab / ThinkOrSwim, IBKR, Tradier

Secondary: Small Proprietary Trading Firms (2–10 traders)

Higher willingness to pay, buys multiple units, qualifies for Enterprise pricing — a high-LTV segment we address in Year 2.

D4. Go-To-Market Strategy

We do not rely solely on expensive paid ads. Our Community-Led Growth strategy is built on a 6-stage self-liquidating funnel called Zero Day Spartan. By offering high-value trading mindset education (free eBooks and a "Pay What You Want" book bundle), we aim to drastically reduce our net CAC (as frontend book sales offset ad spend). Once trust is established via our automated email sequences, we upsell the Zedcrit Terminal as the ultimate hardware solution to their trading pain. Crucially: while this funnel is designed for hyper-efficiency, we modeled our financial projections using a highly pessimistic $1,200 CAC (and a realistic $800 CAC), ensuring the business remains highly profitable even in worst-case scenarios.

Dual-Hardware Strategy: By introducing the premium Zedcrit Pro at $1,499, we create a powerful pricing anchor. This market segmentation allows us to capture high-volume traders and prop firms while making the $799 Zedcrit Core feel like exceptional value for entry-level traders, accelerating overall conversion and creating a natural upgrade path.

ScenarioDescriptionEstimated CACLTV/CAC
PessimisticPaid ads + paid influencers exclusively$1,2003.6 : 1
Realistic50% organic / 50% paid mix$8005.4 : 1
OptimisticCommunity-led growth, organic focus$4509.5 : 1
Safety Buffer: Even in our worst-case scenario (CAC $1,200), the LTV/CAC ratio remains an extremely healthy 3.6:1, leaving a wide margin for variance in customer acquisition.

CAC Evolution Simulation

$1,200
$750
$450
Month 1–6
Testing (Paid)
Month 7–12
Optimization (Mix)
Month 13+
Scaling (Organic)
E

Business Model

E1. Revenue Streams
Revenue StreamPriceCostMarginRole
Zedcrit Core (one-time)$799$350~56%Entry-level gateway
Zedcrit Pro (one-time)$1,499$750~50%High-LTV premium tier
Software Maintenance (monthly)$149/mo<$20/mo>85%Primary profit engine
Zedcrit Care (optional)$49/mo<$1/mo~98%Support/replacement revenue
E2. Unit Economics
ComponentMonthlyAverage Lifetime (20 months)
LTV (Zedcrit Core)$4,073
LTV (Zedcrit Pro)$4,773
5.4 : 1
Base case LTV/CAC (blended LTV based on a 70-30 Core/Pro mix vs $800 CAC). Reflects a realistic ~5.0% monthly churn.
<1 mo
Hardware payback period on $799 price point.
$41M
TAM (Total Addressable Market) in US Options alone.

Pricing vs. Competition

SolutionMonthlyAnnual3-Year Total
Zedcrit Terminal ✓$149$2,587 (incl. hardware)$6,163
SpotGamma Enterprise$1,000+$12,000+$36,000+
Cboe Terminal$500+$6,000+$18,000+
Bloomberg Terminal$2,000+$24,000+$72,000+
E3. Pricing Strategy & Psychology
  • $799 Zedcrit Core / $1,499 Zedcrit Pro — The dual-hardware approach anchors the price, making the $799 Core feel like an exceptional bargain while providing a premium option for high-end traders. Both feel like professional, tax-deductible equipment purchases.
  • $149/month — Below the psychological $150/month threshold. Less than most traders already spend on inadequate tools.
  • $49/month Care — Feels optional and affordable. Converts support cost into a ~98% margin revenue stream.
  • Pain-based value framing — "One prevented regime misread pays for the entire system." A $5,000 loss averted makes the upfront cost feel trivial.

Break-even Analysis for a Typical User

MetricValue
Cost total Year 1 (Zedcrit Core)$2,587 ($799 + $149 × 12)
Alternative (SpotGamma + Data)$14,400 ($1,200 × 12)
Annual Saving$11,813
Break-even2.2 months
User reduces costs by 82%: By switching to Zedcrit Terminal, a typical trader saves significant capital on recurring live data and analytics subscriptions.
F

Financial Projections (5 Years)

Downside Protected
-0%
Even in worst case (500 units),
investors only suffer a partial loss (0.5x-0.8x ROI)
High Upside
+300%
Base case: 1.2-1.8x return
Best case: 5-8x+ return
F1. Consolidated 5-Year P&L

Note: Projections assume a ~228% Year-over-Year growth rate in Year 2, supported by our CAC optimization strategy. *New Units Sold includes hardware upgrades and secondary multi-location units purchased by existing clients, outstripping net-new active subscriptions.

MetricYear 1Year 2Year 3Year 4Year 5
New Units Sold852355808901,190
Active Clients652135579901,460
── REVENUE ──
Hardware Revenue$86,115$236,765$605,520$947,710$1,284,010
Software ARR$116,220$380,840$995,920$1,770,120$2,610,480
Care Revenue$11,466$37,570$98,250$174,640$257,540
Total Revenue$213,801$655,175$1,699,690$2,892,470$4,152,030
── COSTS ──
Hardware COGS$40,150$110,750$277,400$431,300$582,100
CAC (Marketing)$60,000$188,000$348,000$623,000$952,000
Operations$40,000$90,000$180,000$350,000$550,000
Salaries / Contractors$72,000$144,000$240,000$500,000$900,000
R&D$20,000$50,000$90,000$150,000$200,000
Legal & Admin$15,000$20,000$30,000$45,000$60,000
Total Costs$247,150$602,750$1,165,400$2,099,300$3,244,100
── RESULTS ──
EBITDA−$33,349$53,925$559,290$888,570$1,117,730
EBITDA Margin−16%8%33%31%27%
Margin Breakdown: Hardware Gross Margin is ~53% (blended Core/Pro mix), preserving a strong margin for shipping, support, and RMA. SaaS Gross Margin scales to 80%-85%.
Conservative Assumption (Unmodeled Upside): This P&L model assumes churned hardware is permanently lost. Revenue generated from SaaS reactivations on the secondary hardware resale market is treated as pure upside and is not modeled here.
*Note: Financial projections employ strict unit-level rounding (e.g., 85 units in Year 1 is modeled exactly as 59 Core and 26 Pro units to preserve whole numbers, rather than a perfect mathematical 70/30 split), which may cause minor sub-1% variances in blended calculations.
Year 1 Note: Revenue figure represents end-of-year software ARR run rate. Actual collected revenue is lower due to mid-year unit onboarding. The company reaches cash-flow positive in Year 2 without additional capital.
Cash Flow Note: Because hardware is drop-shipped via Amazon Fulfillment (requiring zero inventory/working capital) and software subscriptions are pre-paid, EBITDA closely mirrors Operating Cash Flow.
Active Clients Note: "Active Clients" represents the total cumulative base of active subscriptions at year-end, while "New Units Sold" includes entirely new clients, hardware upgrades, and secondary units purchased by existing clients within that specific calendar year. In later years, cumulative Active Clients naturally exceed annual New Units Sold due to compounding retention. Additionally, the unit count difference is explained by reactivations, the secondary market (zero CAC), hardware upgrades, and multi-location purchases. Mathematically: Active (end) = Active (start) + Net New Active - Churn.

Operational Scaling

As we move to volume manufacturing, we are preparing key logistical milestones: finalizing FCC and CE hardware certifications for international shipping, implementing standardized 1-year limited warranties, and scaling a dedicated tier-1 technical support protocol for rapid hardware replacements to minimize downtime for active traders.

F2. Exit Valuation & Target Acquirers

Financial technology and retail trading platforms trade at 10x–15x EBITDA (a conservative multiple for highly profitable Hardware-SaaS hybrids). At Year 5 EBITDA ($1.11M), this yields an expected exit valuation of $11.1M – $16.7M.

Target Acquirers (Retail Fintech)Why they would acquire Zedcrit
Robinhood / WebullTo offer a premium, institutional-grade product to their most active options traders.
TradeStation / TradingViewDeep integration into their existing routing or charting ecosystems to attract options volume.
ScenarioMultipleYear 3 ExitYear 5 Exit
Conservative10x EBITDA$5.6M$11.1M
Optimistic15x EBITDA$8.4M$16.7M
Our EstimateBlended$6–8M$10.4–15.6M
F3. Investor Return Scenarios — Base & Upside

$300K @ $6M cap = 5% initial ownership (~3.5% effective after standard 30% dilution).

Base Case (Conservative — 1,460 clients in Year 5)

ScenarioExit ValuationInvestor Share (Post-Dilution ~3.5%)Return Multiple
Conservative (10x EBITDA)$11.1M$391K1.3x
Optimistic (15x EBITDA)$16.7M$586K2.0x

Upside Case (Aggressive — 3,500+ clients in Year 5)

ScenarioExit ValuationInvestor Share (Post-Dilution ~3.5%)Return Multiple
Conservative (10x EBITDA)$38.0M$1.33M4.4x
Optimistic (20x EBITDA)$76.0M$2.66M8.9x
How we get to Upside:
CAC optimization: If our optimistic $450 CAC materializes, we acquire clients 44% faster.
Prop firm adoption: One prop firm = 5+ units at near-zero marginal CAC.
Broker partnerships: TradingView, Webull, or Robinhood integration unlocks substantial user bases.
Secondary market: Every churned unit resells at $0 CAC — pure upside we don't model.
Pre-seed context: A 1.3x–2.0x base case protects downside. A 4.4x–8.9x upside case delivers VC-grade returns. Milestone-based tranches ensure capital is deployed only upon proven execution. You don't fund speculation — you fund a highly structured, scalable venture.
F4. Sensitivity Analysis — Downside, Base, and Upside
ScenarioYear 5 ClientsYear 5 ARRYear 5 EBITDAExit ValuationInvestor ROI
Worst Case500$894K~$350K$3–5M0.5x–0.8x
Base Case1,460$2.61M$1.11M$11.1–16.7M1.3x–2.0x
Upside Case3,500+$6.26M+$3.8M+$38.0–76M4.4x–8.9x

Key Insight: Even in the worst case (500 units total, 33% of our base case), the company generates ~$350K EBITDA and exits at $3.5–5M — still a ~0.4x–0.6x ROI (partial loss of capital) on a $300K pre-seed investment. The downside is heavily protected. The upside potential is compelling.

G

The Ask — Milestone-Based SAFE

G1. Round Structure

We are raising $300,000 on a SAFE at a $6M Valuation Cap. We proactively propose a Milestone-Based Tranche Structure — capital deployment maps precisely to risk reduction. This tranche structure is explicitly designed to test our actual CAC against our conservative models before scaling capital deployment. You don't fund speculation; you fund proven execution.

TRANCHE 1
The Catalyst
$100,000
R&D $40K · Procurement $25K (20 units + prototypes) · Legal $20K · Buffer $15K

Finalizes Private Beta, establishes legal foundation, deploys first physical units.
Unlock for T2: 20 Terminals live 24/7 + Schwab API live with zero interruptions
TRANCHE 2
Market Validation
$100,000
R&D $30K (IBKR) · Procurement $25K (45 units) · Marketing $30K · Legal $15K (FCC/CE)

Converts beta to paying customers, procures commercial batch. Remaining Year 1 units are funded by incoming cash flow.
Unlock for T3: 85 total units sold + $10K+ MRR from subscriptions
TRANCHE 3
The Scale
$100,000
R&D $30K (Tradier) · Procurement $25K (Future inventory) · Marketing $20K · Ops $25K

Prepares Year 2 volume, expands broker integrations, aggressively acquires customers.
Result: 15–18 months total runway → profitable in Year 2
InstrumentSAFE (Simple Agreement for Future Equity)
Valuation Cap$6,000,000 (locked for all tranches)
Total Raise$300,000
Monthly Burn~$18,000
Runway15–18 months (including revenue offset)
Break-EvenYear 2 (Month ~18)
G2. Use of Funds Summary
CategoryTotal AllocationPrimary Use
R&D$100,000UI/UX finalization, IBKR/Tradier integrations, HMM algorithm updates
Procurement$75,000Acquiring hardware inventory & prototypes
Marketing$50,000Influencer partnerships, community building, paid acquisition tests
Legal & Admin$35,000Entity formation, EULA, patent exploration
Buffer / Ops$40,000Fixed monthly costs, contingency
Total$300,000
G3. Key Milestones
MilestoneTargetTimeline
First commercial unit shipped1 unitMonth 6
85 units sold (Year 1 goal)85 unitsMonth 12
$10K+ MRR from subscriptions~50 active subscribersMonth 10–12
Break-even (EBITDA > $0)~150 active clientsMonth 18
235 new units (Year 2)213 active clientsMonth 24
$500K+ ARR215 active subscribersMonth 24
5+ broker integrationsSchwab, IBKR, Tradier + 2 moreMonth 24
H

Team

H1. Founding Team
Adrian Danet
CEO · Quant Lead · Co-Founder (28% Equity)
Lost $25,000 in a single trading day — then spent years building the system that would have saved him. Brings 15+ years of C-level management experience (COO/CEO), an MBA, and a PhD in Financial Analysis. Combines deep domain expertise in 0DTE SPX options trading with advanced mathematical modeling (HMM, Kalman, GEX analytics). Built the first working prototype.
MBA & PhD in Finance Strategy & Management SPX 0DTE Options Hidden Markov Models Python · Polars
Alina Danet
CFO & Marketing Lead · Co-Founder (28% Equity)
Over 15 years of experience as a Financial Manager and Charted Accountant (CECCAR). Holds a PhD in Financial Management and an MSc in Marketing. Extensive background in international market analysis (US & Japan fellowships). Drives the Community-Led Growth strategy, blending strict financial oversight with targeted marketing acquisition to maintain the 5.4:1 LTV/CAC ratio.
Financial Strategy Marketing & Market Analysis Charted Accountant Community-Led Growth Corporate Finance
Adrian-Ilie Oprișor
CTO · Trading Systems Engineer · Co-Founder (24% Equity)
Expert in Python & C++ algorithmic trading systems and execution infrastructure. Specializes in low-latency event-driven architecture, zero-copy data ingestion (Apache PyArrow), and secure Linux deployments. Responsible for transforming the prototype into a production-grade, fault-tolerant edge appliance using Docker, ClickHouse, and Linux Keyring security.
C++ & Python Algo-Trading ClickHouse & PyArrow Docker · Linux Security Event-Driven Architecture
Note: Co-founders hold 80% equity. The remaining 20% is fully reserved for ESOP (10%) and future rounds (10%).
H2. Hiring Plan (Post-Funding)
PositionTypeTimingCost
UI/UX DeveloperContractor (part-time)Month 2$20K/yr
Customer Support SpecialistContractor (part-time)Month 3$15K/yr
Full-Stack DeveloperFull-time employeeYear 2$70K/yr
Marketing SpecialistFull-time employeeYear 2$60K/yr
Sales / Business DevFull-time employeeYear 3$60K/yr
I

Risk Mitigation

I1. Risk Matrix & Mitigations
RiskLikelihoodImpactMitigation
Schwab blocks retail API / limitsLowHighAbstract DataProvider with UI callbacks. Phase 1: BYOD via Schwab. Phase 2: Premium backup feeds (Databento/Polygon.io) for commercial mitigation.
Competitor copies featuresMediumMediumTPM 2.0 encryption + Trade Secrets + Nuitka compilation. Years and millions to replicate.
Hardware supply chain delaysMediumMediumJIT model with 2–3 unit buffer. Purchasing in bulk at 150+ units eliminates single-source risk.
Hardware failure / RMALowMedium~53% blended hardware margin covers instant overnight replacement. Ultra-silent active cooling + NVMe = highly reliable.
SEC / FINRA complianceLowHighStrictly impersonal analytics. "Statistical Implied Vector" terminology. BYOD model = no data distribution liability.
Slower adoptionMediumMediumOrganic channels first. Tranche structure means capital is only deployed after milestones proven. Worst case still exits at 0.5-0.8x.
IP theft / disclosureLowHighTrade Secret + TPM 2.0 + Nuitka. No public disclosure. Code runs compiled in a sealed system.
High churn (retail blow-ups)LowMedium$799 price naturally filters gamblers. Target: $50K-$500K account holders. Zedcrit helps users survive longer, protecting LTV.
Actual CAC higher than estimatedMediumMediumSafety buffer built in. LTV/CAC remains 3.6:1 even in a pessimistic $1,200 CAC scenario.
Retention lower than estimate (churn > 3%)MediumHighHardware creates psychological "lock-in". Zedcrit Care creates a strong support relationship that increases retention.
J

Investor Materials

J1. Investor Outreach Scripts

For Angel Investors (Ex-Traders)

"I lost $25,000 in a single day — $15K on one account, $10K on another. I thought it was choppy. The market entered a strong downtrend. I didn't recognize the regime shift in time.

From that day, Zedcrit Terminal was born. A hardware appliance running HMM Regime Detection + GEX + market forces, locally, $0 monthly data cost. We drive efficient acquisition through our "Zero Day Spartan" community funnel, yet we modeled the financials on a pessimistic $1,200 CAC (and realistic $800 CAC). 10 traders in Private Beta. Raising $300K at $6M cap. 5-year projections: $2.61M ARR, $10.4–15.6M exit. Do you have 10 minutes for a demo?"

For Micro-VCs (Deep Tech / Hardware)

"We're not selling hardware. We're selling quantitative intelligence. Hardware protects IP (TPM 2.0) and eliminates cloud costs — running this on AWS for 1,500 users would cost $75K–$110K/month. Our edge model costs <$20/user (saving $540K–$954K/year)."

~31% hardware margins, ~85% software margins, LTV/CAC 5.4:1. $10.4–15.6M exit in 5 years. Milestone-based tranches eliminate execution risk. Would you like to see the deck?"

For Traditional VC (Fintech / SaaS)

MetricBase Case (Year 5)Upside Case (Year 5)
ARR$2.61M$6.26M+
EBITDA$1.11M$3.8M+
Exit Valuation$10.4–15.6M$37.6–80M
Investor ROI ($300K @ $6M)1.2x–1.8x4.4x–9.3x

"LTV/CAC 5.4:1. 15–18 months runway. Profitable in Year 2. Milestone tranches protect your capital. Our base case delivers solid returns; our upside case delivers VC-grade multiples. The downside is protected; the upside is massive. The math works — and the growth model is highly asymmetric."

J2. Investor Q&A — Objections & Responses
01 "Why hardware? Why not just a downloadable app?"

Three reasons: IP Protection — Python code on a desktop app can be decompiled. On the Terminal, code runs compiled in a closed, TPM-encrypted system. Our HMM models are physically protected. Stability — Schwab WebSocket ingestion isn't interrupted by Windows updates or other processes. The appliance is dedicated. Performance — Polars and ClickHouse run on dedicated hardware cores. The trader's main PC stays free for execution.

02 "What if Schwab blocks their retail API?"

We have a two-phase data strategy to mitigate platform risk. Phase 1 operates on a Bring-Your-Own-Data (BYOD) model via Schwab, keeping data costs at $0. In Phase 2, we integrate premium institutional feeds like Databento, Polygon.io, or direct OPRA licenses as a commercial backup. The system is isolated from broker-specific code through an abstract DataProvider interface; switching sources requires no rewrite of the math engine.

03 "How do you scale hardware procurement?"

The JIT model is for our validation phase (first 65 units) — zero capital risk. At 150+ units, we leverage bulk volume purchasing to maintain or improve margins. We maintain a 2–3 unit buffer to eliminate delivery risk at all times.

04 "What if a user cancels their subscription?"

Per our EULA, the software license suspends upon payment termination. The Terminal enters Read-Only Mode — historical data accessible, but live stream stops. To resume live trading, the client reactivates the subscription. Hardware without software is useless for active trading. This structurally protects our recurring revenue.

05 "If the hardware is useless without the SaaS, why is there a 23% annual churn?"

1. Trading Attrition: Retail trading has a natural mortality rate. Traders occasionally "blow up" their accounts by breaking their own risk rules. When they lose their capital, they pause the subscription. A 54% annual retention in retail trading is exceptionally strong.

2. The Resale Market (Zero CAC): If a trader quits, they don't throw away a $799 device. They resell it to another trader on eBay or Discord. To unlock the device, the new owner must activate the $149/mo SaaS. Essentially, a churned user's hardware automatically acquires a new user for us at a $0 net CAC.

06 "Aren't you just a Mini PC with software?"

If we were just a Mini PC with software, we'd be vulnerable to copying. We're not. The value is: (1) The mathematical models — HMM, Kalman, forces synthesis. (2) The IP protection — TPM 2.0 makes extraction infeasible. (3) The integration — seamless Schwab data flow. (4) The user experience — zero setup, zero technical skill. Hardware is the vehicle. Software is the value.

07 "SEC risk — could this be considered investment advice?"

Our analytics are strictly impersonal — they don't consider the user's risk profile, portfolio size, or financial goals, which is the fundamental SEC threshold for investment advice. We use "Statistical Implied Vector" (not "Predicted Target"). We use "Historical Probability Level" (not "Trade Signal"). The decision to buy or sell remains 100% an independent human decision. Zedcrit is a quantitative indicator — like RSI or a Moving Average, just far more sophisticated.

08 "$799 upfront creates conversion friction — how do you sell it?"

We position it as professional, tax-deductible trading equipment — not a subscription. The psychological trigger is pain prevention: when an active options trader loses $5,000 from one bad regime misread, $799 feels completely trivial. Our Private Beta already validates that traders suffering from misread regimes consider a sub-$1,000 upfront cost a bargain to stop the bleeding. Our ~53% blended hardware margin covers the cost effortlessly. The Terminal is designed for reliability: ultra-silent active cooling + NVMe. Before shipping, every unit undergoes an automated Burn-in QA (SMART, Memtest, 100% CPU stress test). We also use a Master Recovery Key Registry to instantly recover client data on new hardware, and a Remote Kill-Switch to wipe stolen units. The Zedcrit Care $49/month tier converts potential support issues into a profitable ~98% margin revenue stream.

09 "How do you manage support for 1,000+ local devices without huge scaling costs?"

We operate a self-hosted VPN network (using NetBirds / WireGuard). Commercial VPNs like Tailscale/Twingate would cost $700+/month for a 1,000-unit fleet. By self-hosting, we eliminate per-node scaling costs while maintaining secure, persistent connections for telemetry and remote support. Clients can also use this secure tunnel to access their Terminal remotely.

10 "Why not just raise a prop fund and trade the model yourself?"

A SaaS business with >85% margins and 5:1 LTV/CAC generates compounding, risk-free cash flow. A prop fund carries systemic risks — black swans, broker outages, gap-downs — that no model can perfectly predict. A scalable financial data company trades at 4–6x ARR. A prop fund trades at 1–2x book. Selling the "picks and shovels" during a gold rush is always the better business.

11 "Why would a SaaS giant acquire you?"

They acquire us for the mathematical models — HMM + Forces synthesis — validated on thousands of hyper-active, profitable retail traders. Hardware is our moat while we're a startup vulnerable to IP theft. At exit, our technology is extracted from hardware into the acquirer's secure cloud infrastructure. They buy proven, battle-tested algorithmic IP and a captive, high-LTV customer base.

12 "How do you address data privacy and security concerns?"

Data security is a core pillar of our architecture. The Terminal operates locally on the user's network and connects directly to the brokerage API using encrypted OAuth flows. No sensitive trading data or positions are ever routed through our central servers. Additionally, the hardware is secured via TPM 2.0 and LUKS full-disk encryption, making physical extraction infeasible.

13 "Why is now the right time to invest?"

1. 0DTE Explosion: 0DTE options now account for over half of all SPX volume, making real-time regime detection a mandatory requirement, not a luxury.

2. Privacy Backlash: Retail traders are increasingly rejecting cloud platforms that harvest their trading data. Our local architecture solves this natively.

3. Accessible Hardware: Mini PCs (like Ryzen 7 / Core Ultra) with 32GB RAM make our ~53% blended hardware margin possible via Amazon Prime, eliminating inventory risk.

4. First-Mover Advantage: We are the first to package institutional quant logic into a standalone, $0-data-cost edge appliance for retail.

Now is the time to invest.

K

Appendix

K1. Glossary of Terms
TermDefinition
0DTEZero Days To Expiration — options expiring the same trading day
HMMHidden Markov Model — probabilistic state machine for regime detection
GEXGamma Exposure — measure of dealer positioning from options flows
Call WallStrike with highest call open interest — acts as resistance
Put WallStrike with highest put open interest — acts as support
Gamma FlipLevel where dealer gamma positioning shifts from positive to negative
VannaSecond-order Greek — how delta changes with implied volatility
CharmSecond-order Greek — how delta changes with time (theta decay of delta)
Liquidity VoidPrice zone with minimal dealer hedging — prices move fast through these
Kalman FilterOptimal recursive estimator for noisy data streams
BYODBring Your Own Data — client uses their own API key; no data distribution liability
SAFESimple Agreement for Future Equity — convertible investment instrument
ARRAnnual Recurring Revenue — annualized software subscription revenue
LTVLifetime Value — total revenue expected from a single customer (20-mo: $4,073)
CACCustomer Acquisition Cost — total cost to acquire one paying customer
TPM 2.0Trusted Platform Module — hardware security chip; makes IP extraction infeasible
LUKSLinux Unified Key Setup — full-disk encryption layer
OPRAOptions Price Reporting Authority — data licensing body for options chain data
BKMBakshi-Kapadia-Madan — model-free implied variance framework
GPDGeneralized Pareto Distribution — extreme value theory for tail risk
WelfordWelford's Online Algorithm — single-pass real-time variance calculation
K2. Technical Specifications

Hardware: Zedcrit Core (Base Model)

ComponentSpecification
ProcessorIntel N100 (Efficient 4-core)
RAM16 GB DDR5
Storage256 GB NVMe SSD (zero moving parts)
EncryptionLUKS Full Disk + TPM 2.0 hardware binding
DisplayTuring Smart Screen (status, temps, connectivity indicator)
CoolingUltra-silent passive cooling
NetworkGigabit Ethernet
Power65W USB-C
Dimensions~4" × 4" × 2" · ~1.5 lbs

Hardware: Zedcrit Pro (Performance Model)

ComponentSpecification
ProcessorIntel Core i5 or AMD Ryzen 5 (6–12 cores)
RAM32 GB DDR5
Storage1 TB NVMe SSD (zero moving parts)
EncryptionLUKS Full Disk + TPM 2.0 hardware binding
DisplayTuring Smart Screen (status, temps, connectivity indicator)
CoolingUltra-silent active cooling (necessary for 32GB DDR5 / Ryzen 7 load)
NetworkGigabit Ethernet
Power65W USB-C
Dimensions~4" × 4" × 2" · ~2 lbs

Software Stack

LayerTechnology
OSLinux (hardened, minimal attack surface)
OrchestrationDocker Compose (K3s for Phase 4 scale)
DatabaseClickHouse (high-performance columnar)
ProcessingApache PyArrow + Polars (vectorized, zero-copy)
API ServerFastAPI (async, WebSocket)
DashboardReact (served at zedcrit.local — no app install)
CompilationNuitka (prevents Python decompilation)
Math EnginesHMM · Kalman Filter · Black-Scholes Greeks · Forces Synthesis
CONFIDENTIAL — INVESTOR USE ONLY
This document is confidential and intended solely for the individual or entity to whom it is addressed. Any unauthorized review, use, disclosure, or distribution is prohibited. This document contains proprietary information and trade secrets of Zedcrit. This is not an offer to sell or a solicitation of an offer to buy any securities. Past performance and financial projections are not guarantees of future results.

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We are raising $300K on SAFE @ $6M cap, structured in 3 milestone-based tranches of $100K each.

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