Software Alternatives, Accelerators & Startups

Spyne.ai VS Amazon Machine Learning

Compare Spyne.ai VS Amazon Machine Learning and see what are their differences

Spyne.ai logo Spyne.ai

Spyne is helping businesses create high-quality product visuals at scale with AI.

Amazon Machine Learning logo Amazon Machine Learning

Machine learning made easy for developers of any skill level
  • Spyne.ai Landing page
    Landing page //
    2023-10-19

One of the biggest pain points for any online seller is to showcase their products in the best possible manner to grab customer attention and increase conversions.

Spyne is transforming the way businesses create their catalog using state-of-the-art AI technology. No studio. No photography skills. No complex processes. Just Spyne to create stunning catalogs that drive 40% better conversions.

We are building first-of-its-kind AI that would transform the way businesses will create high-impact catalogs without the need for a physical studio.

We are building computer vision and AI technology to automate image processing workflows. This will help any business or marketplace shoot, edit, and publish product visuals at scale, at a fraction of the cost, and time.

We are helping large e-commerce marketplaces in the automotive, food, fashion, real estate, and retail industry create and upgrade high-quality visual catalogs at scale.

Founded in 2018, Spyne is headquartered in Gurugram, India serving 80+ customers across 15+ countries including Amazon India, Flipkart, Karvi, OLACars, Sell Any Car, etc. We are backed by Accel Partners, Storm Ventures, and other marquee investors.

  • Amazon Machine Learning Landing page
    Landing page //
    2023-03-13

Spyne.ai

Website
spyne.ai
$ Details
freemium $0.07 (Credits)
Platforms
Android Google Chrome Windows iOS Safari iPhone
Release Date
2018 March

Spyne.ai videos

[Tutorial] How to use SpyneAI App to Shoot your Car Images

Amazon Machine Learning videos

Introduction to Amazon Machine Learning - Predictive Analytics on AWS

More videos:

  • Tutorial - AWS Machine Learning Tutorial | Amazon Machine Learning | AWS Training | Edureka

Category Popularity

0-100% (relative to Spyne.ai and Amazon Machine Learning)
Photography
100 100%
0% 0
AI
15 15%
85% 85
Photo Editing
100 100%
0% 0
Developer Tools
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Amazon Machine Learning seems to be more popular. It has been mentiond 2 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Spyne.ai mentions (0)

We have not tracked any mentions of Spyne.ai yet. Tracking of Spyne.ai recommendations started around Mar 2021.

Amazon Machine Learning mentions (2)

  • Rant + Planning to learn full stack development
    There’s also the ML as a service (MLaaS) movement that lowers the barrier for common ML capabilities (eg image object detection and audio transcription). Basically, you use APIs. See: https://aws.amazon.com/machine-learning/. Source: almost 2 years ago
  • Ask the Experts: AWS Data Science and ML Experts - Mar 9th @ 8AM ET / 1PM GMT!
    Do you have questions about Data Science and ML on AWS - https://aws.amazon.com/machine-learning/. Source: over 3 years ago

What are some alternatives?

When comparing Spyne.ai and Amazon Machine Learning, you can also consider the following products

PhotoAiD - Take passport photos where and when you want!

Machine Learning Playground - Breathtaking visuals for learning ML techniques.

FocoClipping - FocoClipping is an online free-to-use image background remover, the key features are as follows : 1. Remove image background 100% automatically. 2. HD output quality up to 3000x 3000 pixels. 3. One click to change backgrounds with new backgrounds.

Lobe - Visual tool for building custom deep learning models

Cutout.Pro - Retouch photo online & magically remove unwanted elements

Apple Machine Learning Journal - A blog written by Apple engineers