
Vectorizer.io
Vector Magic
Autotracer.org
PerfectVector
potrace
Vectorizo
Inkscape
AI image to vector converter for logos and graphics. Turn PNG and JPG into clean SVG vectors instantly. Built for designers, developers and marketers who need scalable, crisp assets for web, apps, print and branding.
LayerStack’s Arm-based cloud virtual machines, powered by cloud-optimized CPU based on Arm architecture that deliver excellent cost-effective processing power, allowing you to easily complete the most demanding application development.

Website, pricing, platforms and company facts side by side.
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| Website | vectorgram.ai | layerstack.com |
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| Company | 2026 | — |
| Listed in |
In their own words, as submitted to SaaSHub.

Vectorgram.ai is an AI-powered vectorizer that converts raster images (PNG, JPG) into clean, scalable SVG vectors in seconds. It is optimized for logos, icons and brand assets, delivering high-quality results without manual tracing. Designers, developers and marketers use Vectorgram to create...
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As answered by people managing vectorgram.ai and LayerStack Arm-based Cloud Server.
vectorgram.ai's answer
Vectorgram focuses on real workflows, not just “image to SVG”. It supports batch processing, has a REST API and handles gradients well. It’s optimized for logos and brand assets, so you get clean, usable SVGs without hours of manual cleanup.
vectorgram.ai's answer
If you need production-ready SVGs for logos and branding, Vectorgram saves a lot of time. Batch processing and an API let you integrate it into your workflow, and the output usually needs far less manual fixing than with generic converters.
vectorgram.ai's answer
Designers, developers and small teams working with logos and brand assets, plus makers who prepare files for laser cutting, CNC and embroidery. All of them need clean, scalable SVGs for digital and physical production.
vectorgram.ai's answer
We built Vectorgram because converting logos to clean SVGs was too painful. Most tools either trace badly or require a lot of manual work, so we focused on batch processing, an API and good gradient support to make this part of the workflow actually fast.
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