AMD ROCm Migration Coach

3.60

Derivation Chain

Step 1 Meta-AMD large-scale AI chip contract

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Step 2 AMD GPU adoption increase

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Step 3 CUDA→ROCm code migration

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Step 4 ROCm migration automation tool

Problem

With Meta's large-scale AMD adoption driving a surge in the AMD GPU ecosystem, a growing number of Korean AI development teams (2-10 people) are looking to migrate existing NVIDIA CUDA-based AI code to AMD ROCm. However, 30-40% of CUDA-exclusive libraries, custom kernels, and optimization tricks are incompatible with ROCm, and manual migration takes 2-8 weeks depending on codebase size.

Solution

A CLI/web tool that analyzes uploaded CUDA codebases for ROCm compatibility and auto-generates replacement code for incompatible sections. Goes beyond HIPify by analyzing custom kernels and third-party library dependencies, and automatically runs performance regression tests after migration.

Target: ML engineers (2-5 years experience) at Korean AI Startups running CUDA-based AI services

Revenue Model: ~$290 Per Transaction for code analysis (up to 100K lines). Auto-generated migration code additional ~$440 Per Transaction. Monthly flat rate (unlimited analysis) at ~$111/month.

Ecosystem Role: Supplier

MVP Estimate: 1_month

NUMR-V Scores

N Novelty

4.0/5

U Urgency

5.0/5

M Market

4.0/5

R Realizability

2.0/5

V Validation

4.0/5

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 (60%)

Tech Complexity

24.7/40

Data Availability

23.1/25

MVP Timeline

12.0/20

API Bonus

0.0/15

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 (54/100)

Competition

8.0/20

Market Demand

6.2/20

Timing

14.0/20

Revenue Signals

10.5/15

Pick-Axe Fit

10.5/15

Solo Buildability

5.0/10

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

Backend [high] AI/ML [medium] Frontend [low]

Dashboard