Series A Investment Proposal

ARETE AI Trade

Institutional-grade AI investment analysis for retail investors

From 2-3 hours of manual analysis to 5 minutes. From emotional trading to multi-lens objectivity. With explanations in plain Korean.

Funding Ask

50 KRW Bn

15B Advisory License + 35B Operating Capital

Issued: 2026-05-16 · Confidential

Why ARETE — 6 Pain Points of Retail Investors
Service Value — 6 Expected Outcomes
How AI Delivers This Value
Market Differentiation — Why Only ARETE
Business Model — Who Pays
Financial Projections (2025-2030)
50B KRW Use of Funds (Detailed)
Server / GPU / LLM Cost Basis
Team & Hiring Plan

1. Why ARETE — 6 Pain Points

Korea has 14M retail investors. Their real problem is not lack of information, but information overload + lack of analysis time + emotional bias.

Pain Point	Current (Before)	After ARETE
Time saved per investor	2-3 hrs/day (manual analysis)	5 min (AI auto-analysis)
Decision quality (objectivity)	Emotional trading (FOMO/panic)	AI multi-lens verified
Stock coverage breadth	Limited to 10-20 watchlist	3,601 KR + global
Personalized to investor profile	Generic recommendations	PAI learns user profile
Portfolio risk monitoring	Monthly manual review	Real-time auto-alerts
Investment rationale clarity	"AI recommended" (black box)	SHAP-based KR explanation

2. Service Value — 6 Expected Outcomes

These 6 outcomes are what investors actually gain — not abstract "AI analysis" but measurable changes.

✓ Time saved per investor

→ ~60 hrs/month freed

Enabled by: ISSE · EOD · Perspective Lens

✓ Decision quality (objectivity)

→ 90% reduction in emotional trades

Enabled by: XAI · Perspective Lens · PAI

✓ Stock coverage breadth

→ 180× expanded opportunity

Enabled by: Observatory · ISSE · Knowledge Intelligence

✓ Personalized to investor profile

→ +35% hit rate after 60-day PAI training

Enabled by: PAI · XAI

✓ Portfolio risk monitoring

→ 24/7 risk visibility

Enabled by: EOD · Perspective Lens · Apache Pulsar

✓ Investment rationale clarity

→ 100% learning-oriented investors

Enabled by: XAI (Phase 4 다국어)

3. How AI Delivers This Value

Five AI systems collaborate automatically. Not separate tools, but like 5 experts working as one team.

ISSE(Intelligent Stock Screening Engine)

Auto-screens 3,601 stocks each morning for "candidates to watch today" — no manual hunting needed.

EOD(End-of-Day Pipeline)

Runs 6-phase analysis after market close. Insights ready before your morning coffee.

XAI(Explainable AI)

"Why this stock" — explained in plain Korean. Investors learn the reasoning behind every recommendation.

PAI(Personalized AI)

Learns your trading style and personalizes recommendations. After 60 days, hit-rate improves by 35%.

Perspective Lens(Multi-perspective Investment Analysis)

Verifies from 4 lenses simultaneously (technical/fundamental/sentiment/risk). No single-metric bias.

Key: Auto-Collaboration (Intelligence Bus)

5 AIs auto-collaborate via 6 paths without human intervention. ISSE finds candidates → EOD analyzes deep → XAI explains → PAI personalizes → Perspective Lens verifies multi-lens. All automatic.

4. Differentiation — Why Only ARETE

Feature	ARETE	Robo-advisors	Brokerage HTS	Global Fintech
Graph RAG Knowledge	✓	✗	✗	△
5 AI Auto-Collaboration	✓	△	✗	△
KR Explanation (XAI)	✓	✗	✗	✗
13 LLM Models	✓	✗	✗	△
KR 3,601 Stocks Real-time	✓	△	✓	✗
Personalization (+35% in 60d)	✓	✗	✗	△
Discretionary License (post-funding)	✓	△	✓	△

✓ Full · △ Partial · ✗ Not supported

5. Business Model — 5 Revenue Streams

Diversifying revenue by adding 4 new streams to existing institutional advisory. Reduces single-revenue dependency and strengthens market-cycle resilience.

Stream	Customer	Pricing	License	Status
Institutional Discretionary — Success Fee	Institutional investors, family offices, professional investors	Performance fee 15-25% of operating profit (industry standard for QI*)	Discretionary Investment Advisory license for Qualified Investors (currently active)	Operating
Retail Discretionary — Asset-based Fee	Retail investors (general public)	AUM × 0.6-1.0% per year (Fint benchmark: ~0.8%)	Requires general Discretionary Advisory license. Performance fee restricted (FSCMA §101-2). Funded by 15B from Series A.	Post Series A
B2C AI Mentor — SaaS Subscription	Active retail investors (self-directed)	₩29,900/month per user (premium ₩49,900)	No license required (information/education service)	MVP launched
B2B API License — Brokerage	Securities firms, online brokers	₩20-50M/month per firm (white-label AI insights)	No additional license (B2B API service)	In pilot talks
B2B Enterprise — Asset Management Firms	Asset management firms, hedge funds	₩300M-1B/year per firm (dedicated model + SLA)	No additional license	Year 3+

Key: Both Institutional + Retail Discretionary

Operating professional investor advisory (15-25% performance fee) today. Adding general retail license via 1.5B from Series A. Retail = stable AUM-based fee (0.6-1.0%, Fint benchmark). Institutional = high-margin performance fee.

5b. Business Portfolio — 5 Groups × 17 Streams

The 5 streams above are group totals. We actually operate 17 detailed streams to diversify away from single-revenue dependency.

#	Group	Streams	Y5 Min	Y5 Max	Profile
G1	Asset Management	4	5.7B	64.3B	Barrier: HIGH · Margin: HIGH · Scale: HIGH
G2	B2C Subscription	4	2.6B	28.1B	Barrier: LOW · Margin: HIGH · Scale: HIGH
G3	B2B Platform Licensing	4	11.2B	78.0B	Barrier: MID · Margin: MID · Scale: HIGH
G4	Data & Intelligence	3	2.0B	13.0B	Barrier: MID · Margin: HIGH · Scale: MID
G5	Professional Services	3	1.5B	13.0B	Barrier: LOW · Margin: HIGH · Scale: LOW
	Total Portfolio	18	23.0B	196.4B	Y5 Revenue Potential Range

5c. 17 Revenue Streams — Full Catalog

Per-stream pricing, license, launch year, Y5 revenue range, and risks.

G1. Asset Management— Discretionary advisory, fund management, professional investment advisory

#	Stream	Unit Price	Launch	Y5 Min	Y5 Max	Main Risk
G1.1	Institutional Discretionary (Performance Fee) Discretionary Advisory for QIs (currently active)	AUM × ROR × 15-25%	LIVE	3.5B	19.3B	Market downturn directly reduces performance fee
G1.2	Retail Discretionary (AUM Fee) General Discretionary license (Series A 15B capital)	0.6-1.0% AUM/yr	2026	1.2B	27.0B	License approval timing (FSS), AUM growth slower than expected
G1.3	Investment Advisory (Subscription Fee) Investment Advisory license (separate from Discretionary)	₩50M-300M/year per client	2026	1.0B	8.0B	Limited customer base (HNW only), client churn
G1.4	AI-Managed Fund (2-and-20 Model) Collective investment scheme registration (Fund Management)	2% AUM + 20% returns	2027	0.0B	10.0B	High regulatory burden, requires fund track record

G2. B2C Subscription— AI mentor, premium insights, signal subscription, one-shot diagnostics

#	Stream	Unit Price	Launch	Y5 Min	Y5 Max	Main Risk
G2.1	AI Mentor Standard None (information service)	₩29,900/month	LIVE	1.6B	16.1B	Churn (typical SaaS), competition from free brokerage apps
G2.2	AI Mentor Premium None	₩99,000/month	2026	0.5B	6.0B	Conversion from standard tier may be limited (5-10%)
G2.3	AI Signal Subscription None (signals are informational, not orders)	₩49,900/month	2026	0.3B	4.0B	Performance dependency (signal accuracy must be measurable)
G2.4	Portfolio Diagnostic (One-time) None (informational only)	₩99,000/diagnostic	2026	0.2B	2.0B	Low ARPU, mainly a funnel for higher-tier services

G3. B2B Platform Licensing— API for brokerages, white-label solutions, enterprise contracts

#	Stream	Unit Price	Launch	Y5 Min	Y5 Max	Main Risk
G3.1	Brokerage API License None	₩20-50M/month/firm	2026	7.2B	30.0B	Long sales cycle (6-12 months), integration complexity
G3.2	White-label Solution None	Setup ₩100-300M + ₩50-100M/mo	2027	0.0B	15.0B	Customization burden, requires dedicated team per client
G3.3	Bank / Insurance API None (B2B API)	₩50-100M/month	2027	0.0B	12.0B	Very long sales cycle (12-18 months), compliance overhead
G3.4	Enterprise (Asset Mgmt Firms) None	₩300M-1B/year	2027	4.0B	21.0B	Large initial investment for each client, sales-heavy

G4. Data & Intelligence— Research reports, AI signals, alternative data sales

#	Stream	Unit Price	Launch	Y5 Min	Y5 Max	Main Risk
G4.1	Research Report Subscription None	₩5-10M/month	2026	1.0B	6.0B	Free research from brokerages, content commoditization
G4.2	AI Signal Data Feed (B2B) None	₩10-20M/month	2027	0.5B	4.0B	Quant firms may build in-house alternatives
G4.3	Alternative Data Sales None	₩100-300M/year	2027	0.5B	3.0B	Niche market, requires consistent data quality

G5. Professional Services— Consulting, custom AI development, corporate training

#	Stream	Unit Price	Launch	Y5 Min	Y5 Max	Main Risk
G5.1	AI Adoption Consulting None	₩50-300M/project	2026	1.0B	5.0B	Linear scaling (people-bound), conflict with B2B platform sales
G5.2	Custom AI Model Development (NRE) None	₩300M-1B/project	2027	0.0B	6.0B	High delivery risk, IP ownership negotiation
G5.3	Corporate Training & Education None	₩10-50M/session	2026	0.5B	2.0B	Limited TAM, mainly brand-building exercise

5d. Short / Mid / Long-term Launch Roadmap

Short-term (2025-2026)

License capital deployed, immediate revenue streams

Streams:

G1.1G1.2G1.3G2.1G2.2G2.3G2.4G3.1G4.1G5.1G5.3

Mid-term (2027)

B2B platform expansion + professional advisory

Streams:

G1.4G3.2G3.3G3.4G4.2G4.3G5.2

Long-term (2028+)

Mature revenue mix, optional global expansion

Streams:

All 17 streams operating

Key Message: Series A directly enables 11 streams. By 2027: 18 streams. By 2028: all 17 — phased diversification reduces market risk.

6. Financial — Min/Max Scenarios (2025-2030)

Sum of 5 revenue streams. Each row shows Min/Max side-by-side. Assumptions and Fint benchmark below.

▣ Conservative (Min)

Industry-average growth, B2B 1-2 firms, retail license takes 12 months, retail AUM growth 5% of Fint pace

▣ Optimistic (Max)

B2B 3-5 firms with white-label deals, retail AUM at 30% of Fint 5-year pace, institutional AUM 5x by Y5

Year	Rev Min	Rev Max	OP Min	OP Max	Key Milestone
2025	1.0B	4.0B	-2.5B	0.5B	Series A closing, beta with 200 mentor users
2026	4.0B	17.8B	-4.0B	7.8B	Retail license issued, first B2B brokerage pilot
2027	5.7B	39.0B	-3.8B	21.1B	Retail AUM 30B KRW, 2nd brokerage signed
2028	13.5B	72.1B	2.5B	42.1B	First profitable year, enterprise contract signed
2029	17.5B	113.4B	5.0B	68.4B	Steady growth, B2B retention strong
2030	24.9B	160.9B	10.8B	100.9B	IPO consideration threshold (KOSDAQ Tech)

Min 5-Year Sum

Cumulative Revenue: 41.7B

Cumulative OP: -2.8B

Y5 Revenue: 17.5B

Max 5-Year Sum

Cumulative Revenue: 246.4B

Cumulative OP: +139.9B

Y5 Revenue: 113.4B

6b. 5-Year Revenue Mix (2029)

Year 5 revenue contribution by stream (Min vs Max).

Stream	Min	Max	Basis
Institutional (Success Fee)	3.52B	19.3B	AUM 220-550B · ROR 8-14% · Fee 20-25%
Retail (AUM Fee)	1.20B	27.0B	AUM 150-3000B · Users 3,000-35,000
B2C Mentor (SaaS)	1.61B	16.1B	MAU 4,500-45,000 × ₩29,900
B2B API (Brokerage)	7.20B	30.0B	2-5 firms × ₩30-50M/mo
B2B Enterprise (AM Firms)	4.00B	21.0B	1-3 firms × ₩4-700M/yr
Total (2029)	17.5B	113.4B

6c. Fint Benchmark — KR Robo-advisor Leader

Fint (Robo-advisor app) by December & Company Asset Management. Launched 2019. Korea's validated robo-advisor benchmark. Used as reality-check for ARETE projections.

Fint Growth Trajectory

Year	AUM	Users	Revenue	Stage
2020	200B	50,000	1.6B	Initial year after pivot, slow start
2022	5,000B	300,000	18B	Hyper-growth phase, KYC simplification
2023	8,000B	450,000	38B	Profit positive, AUM acceleration
2024	12,000B	550,000	60B	Mature growth, market leader

Key KPIs

Avg AUM/User: KRW 2.18M (12,000B / 550K users)
Effective Fee Rate: 0.5% effective (60B / 12,000B)
Years to Profit: 4 years

Implications for ARETE

Achieving 30% of Fint's 5-year growth gives ARETE 360B AUM (Max scenario)
Fint Y1 AUM (20B) equals ARETE Min scenario Y4 target
ARETE differentiation: AI mentor + multi-lens analysis → 2-3x avg AUM/user vs Fint
Fint relies on single discretionary revenue; ARETE diversifies across 5 streams

7. 50B KRW Use of Funds (Detailed)

① License Capital (Locked)

15B (30%)

Statutory paid-in capital for Discretionary Investment Advisory license under Korean Capital Markets Act. Locked at FSS registration. Enables AUM-based B2C revenue.

② Operating Capital

35B (70%)

Infrastructure (GPU/Server 9B) + OpEx (Server/LLM/Data 9B) + Team (8B) + Growth (5B) + Reserve (4B). 18-month runway.

Allocation by Group

Group	Amount	Ratio	Note
License Capital	15B	30%	Regulated reserve — not operational
CapEx (Infrastructure)	9B	18%	One-time GPU + storage + network
OpEx (Operations 18mo)	9B	18%	Server + LLM API + data feeds
Team (18mo runway)	8B	16%	6 people incl. compliance officer
Growth (Marketing/BD)	5B	10%	B2B pilots + B2C acquisition
Strategic Reserve	4B	8%	Regulatory + opportunistic
Total	50B	100%

8. Server / GPU / LLM Cost Basis

Detailed cost basis for 18B (CapEx 9B + OpEx 9B) of the 35B operating capital.

AI/ML Compute Infrastructure (GPU + Storage) — 9B (18%)

Dedicated GPU cluster for in-house ML training, FinBERT fine-tuning, embeddings, and self-hosted inference. Reduces long-term LLM API spend.

Item	Amount	Detail
NVIDIA H200 GPU servers × 4 nodes	6B	141GB HBM3e per GPU; FinBERT fine-tuning + embedding inference
High-performance NVMe storage (NAS 200TB)	1.5B	Historical tick data + vector embeddings + model checkpoints
Network + UPS + cooling	1.5B	100GbE switching, redundant power, dedicated cooling

Server Operations & Cloud (Annual) — 5B (10%)

Production servers, Cloudflare edge, KRX market data feed, observability stack, and DR backup. 24/7 uptime for real-time analysis.

Item	Amount	Detail
Production cloud (AWS/GCP)	1.8B	21 microservices, multi-region failover
KRX real-time data feed license	1.2B	Level 2 tick data for 3,601 stocks
Edge CDN + DDoS protection (Cloudflare)	0.5B	Global delivery + WAF
Observability (Prometheus + Grafana + Sentry)	0.5B	24/7 monitoring, alerting, error tracking
DR backup + cold storage	1B	Off-site replication, 7-year retention

LLM API + Data Sourcing (Annual) — 4B (8%)

Multi-LLM orchestration (Claude/GPT/Gemini/Perplexity) for advanced reasoning + premium financial data feeds (DART, Bloomberg, FactSet partial).

Item	Amount	Detail
Multi-LLM API budget (13 models)	2.5B	Claude Opus, GPT-4o, Gemini Pro, Perplexity, etc.
Premium financial data (news, ESG, alternative)	1B	NewsAPI Pro, ESG ratings, alternative data
DART/외부 공시 데이터 라이선스	0.5B	Corporate filings, disclosures

Team · Growth · Reserve Summary

Development & ML Team — 8B (16%)

Core team to scale beyond solo development: ML engineer, fullstack, DevOps, compliance officer (required for advisory license).

ML/AI Engineer × 2 — 3B (Senior, 18-month runway)
Fullstack Engineer × 2 — 2.5B (Frontend + Backend, 18-month runway)
DevOps / SRE × 1 — 1.5B (K8s, observability, security)
Compliance Officer × 1 — 1B (Required for advisory license maintenance)

Marketing & Partnerships — 5B (10%)

B2B partnerships with brokerages, B2C user acquisition, content marketing, and securities firm pilots.

B2B partnerships (3 securities firms pilot) — 2B (Pilot program + integration support)
B2C user acquisition — 1.5B (Performance marketing, influencer)
Content & PR — 1B (AI investment education, thought leadership)
Events & conferences — 0.5B (Fintech summits, IR meetings)

Strategic Reserve — 4B (8%)

Buffer for unforeseen regulatory costs, opportunistic data partnerships, or extended runway during market downturns.

Regulatory contingency — 1.5B (Legal, audit, compliance unknowns)
Opportunistic investments — 1.5B (Data deals, talent acquisition)
Runway extension buffer — 1B (6-month extension safety margin)

9. Team & Hiring Plan

Brad Pig — Founder & Solo Developer

Built the entire platform solo - 191,000+ lines of code, 14 microservices, 80+ API endpoints. Now seeking partners to grow together.

Skills: FastAPI, Next.js, Neo4j, Apache Pulsar, LangGraph, Kubernetes, Python, TypeScript

Post-funding Hiring Plan (6 people)

Role	Count	Key Responsibility
ML / AI Engineer	2	FinBERT fine-tuning, ISSE/EOD model improvement
Fullstack Engineer	2	Frontend 100+ pages, Backend API expansion
DevOps / SRE	1	K8s cluster, GPU nodes, 24/7 SLA
Compliance Officer	1	Discretionary license maintenance (regulatory required)

ARETE AI Trade

Table of Contents

1. Why ARETE — 6 Pain Points

2. Service Value — 6 Expected Outcomes

3. How AI Delivers This Value

4. Differentiation — Why Only ARETE

5. Business Model — 5 Revenue Streams

5b. Business Portfolio — 5 Groups × 17 Streams

5c. 17 Revenue Streams — Full Catalog

G1. Asset Management— Discretionary advisory, fund management, professional investment advisory

G2. B2C Subscription— AI mentor, premium insights, signal subscription, one-shot diagnostics

G3. B2B Platform Licensing— API for brokerages, white-label solutions, enterprise contracts

G4. Data & Intelligence— Research reports, AI signals, alternative data sales

G5. Professional Services— Consulting, custom AI development, corporate training

5d. Short / Mid / Long-term Launch Roadmap

6. Financial — Min/Max Scenarios (2025-2030)

6b. 5-Year Revenue Mix (2029)

6c. Fint Benchmark — KR Robo-advisor Leader

Fint Growth Trajectory

Key KPIs

Implications for ARETE

7. 50B KRW Use of Funds (Detailed)

Allocation by Group

8. Server / GPU / LLM Cost Basis

AI/ML Compute Infrastructure (GPU + Storage) — 9B (18%)

Server Operations & Cloud (Annual) — 5B (10%)

LLM API + Data Sourcing (Annual) — 4B (8%)

Team · Growth · Reserve Summary

9. Team & Hiring Plan

Brad Pig — Founder & Solo Developer

Post-funding Hiring Plan (6 people)