A
AI Pitch Deck Builder
4.15
Derivation Chain
Step 1
AI Startup investment expansion
→
Step 2
Startup fundraising tools
→
Step 3
IR deck automation SaaS
Problem
Startup founders at Seed to Series A stage spend 3,000,000–5,000,000 KRW (~$2,250–$3,750) on outsourced design or 2–3 weeks of personal time building investor pitch decks. The biggest pain points are market sizing justification, competitor comparison, and financial projection slides—where founders don't know the format and logical structure investors expect, leading to 3–4 rounds of revision after feedback.
Solution
Input your industry, funding round, and target raise amount → AI auto-generates an investor-perspective pitch deck structure → market sizing slides auto-populated with real proxy data (app downloads, community size, etc.) → VC analyst-perspective feedback simulation. Optimized for the 15–20 slide format preferred by Korean VCs.
NUMR-V Scores
NUMR-V Scoring System
| N Novelty | 1-5 | How uncommon the service is in market context. |
| U Urgency | 1-5 | How urgently users need this problem solved now. |
| M Market | 1-5 | Market size and growth potential from proxy indicators. |
| R Realizability | 1-5 | Buildability for a small team with realistic constraints. |
| V Validation | 1-5 | Validation signal quality from competition and demand data. |
SaaS N=.15 U=.20 M=.15 R=.30 V=.20
Senior N=.25 U=.25 M=.05 R=.30 V=.15
Feasibility (73%)
Data Availability
23.3/25
Feasibility Breakdown
| Tech Complexity | / 40 | Difficulty of core implementation stack. |
| Data Availability | / 25 | Practical availability and cost of required data. |
| MVP Timeline | / 20 | Expected time to ship a usable MVP. |
| API Bonus | / 15 | Bonus for viable public API leverage. |
Market Validation (61/100)
Validation Breakdown
| Competition | / 20 | Signal quality from competitor landscape. |
| Market Demand | / 20 | Demand proxies from search and mention patterns. |
| Timing | / 20 | Fit with current shifts in tech, behavior, and regulation. |
| Revenue Signals | / 15 | Reference evidence for monetization viability. |
| Pick-Axe Fit | / 15 | How well the concept serves participants in a trend. |
| Solo Buildability | / 10 | Practicality for lean-team implementation. |
Technical Requirements
AI/ML [medium]
Frontend [medium]
Backend [low]