How I Built an AI-Powered PNG to SVG Converter with Next.js 14
A technical deep-dive into building VectoSolve: from image processing pipelines to real-time conversion with the Next.js App Router.
Graphics & Design Experts
Our team of experienced designers and developers specializes in vector graphics, image conversion, and digital design optimization. With over 10 years of combined experience in graphic design and web development.
When I started building VectoSolve, I had one goal: make image vectorization accessible to everyone. What seemed like a simple project turned into a deep dive into image processing, AI APIs, and Next.js performance optimization.
Here's exactly how I built it.
The Problem
Converting raster images (PNG, JPG) to vector graphics (SVG) has always been painful:
I wanted something that just works—upload an image, get a clean SVG in seconds.
Tech Stack Decision
Framework: Next.js 14 (App Router)
Database: Supabase (Postgres + Auth)
Payments: Stripe (subscriptions + credits)
Styling: Tailwind CSS
Deployment: Vercel
AI/Processing: Multiple APIs (vectorization, upscaling, background removal)
Why Next.js 14 App Router?
Architecture Overview
The architecture is straightforward but scalable:
The Conversion Pipeline
Step 1: Image Upload
The upload component uses a simple drag-and-drop interface. We validate file types client-side before sending to the server:
const handleDrop = async (e: DragEvent) => {
e.preventDefault()
const file = e.dataTransfer?.files[0]
if (!file) return
if (!['image/png', 'image/jpeg', 'image/webp'].includes(file.type)) {
toast.error('Unsupported format')
return
}
const base64 = await fileToBase64(file)
onUpload(base64, file.name)
}
Step 2: Server-Side Processing
The API route handles authentication, credit verification, and the actual conversion:
export async function POST(request: NextRequest) {
const supabase = createClient()
// Verify user has credits
const { data: { user } } = await supabase.auth.getUser()
const credits = await getUserCredits(user.id)
if (credits < 1) {
return NextResponse.json({ error: 'Insufficient credits' }, { status: 402 })
}
// Process the image
const { image, format } = await request.json()
const result = await vectorizeImage(image, { outputFormat: format || 'svg' })
// Deduct credit and return
await deductCredit(user.id, 1)
return NextResponse.json({ success: true, svg: result.svg })
}
Step 3: Real-Time Feedback
Users see progress updates during conversion. This improves perceived performance even when the actual conversion takes a few seconds.
SEO: 500+ Static Pages
One of VectoSolve's growth engines is programmatic SEO. We generate pages for every conversion type:
/convert/png-to-svg/convert/jpg-to-svg/convert/logo-to-svgPlus, every page is translated into 10 languages using generateStaticParams:
export async function generateStaticParams() {
const locales = ['fr', 'es', 'de', 'pt', 'it', 'nl', 'ru', 'ja', 'ko', 'tr']
const slugs = conversionPages.map(p => p.slug)
const params = []
for (const locale of locales) {
for (const slug of slugs) {
params.push({ locale, slug })
}
}
return params // 10 locales × 21 pages = 210 pages
}
This generates 210 localized pages at build time, all with unique meta content, proper hreflang tags, and FAQ schema.
Performance Optimizations
1. Dynamic Imports
Heavy components load only when needed:
const LogoGenerator = dynamic(
() => import('@/components/LogoGenerator'),
{ loading: () => 2. Image Optimization
Next.js Image component with blur placeholders for instant perceived loading.
3. Edge Runtime
API routes run on the edge, closer to users, cutting response times by 40%.
Lessons Learned
What's Next
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Try it yourself: VectoSolve — Convert your first image free.
Questions? Reach out at contact@vectosolve.com.