Software Alternatives, Accelerators & Startups

Spyne.ai VS Evidently AI

Compare Spyne.ai VS Evidently AI and see what are their differences

Spyne.ai logo Spyne.ai

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

Evidently AI logo Evidently AI

Open-source monitoring for machine learning models
  • 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.

  • Evidently AI Landing page
    Landing page //
    2023-08-19

Spyne.ai

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

Evidently AI

Pricing URL
-
$ Details
-
Platforms
-
Release Date
-

Spyne.ai videos

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

Evidently AI videos

How to Monitor Machine Learning Models (Evidently AI)

Category Popularity

0-100% (relative to Spyne.ai and Evidently AI)
Photography
100 100%
0% 0
Developer Tools
0 0%
100% 100
Photo Editing
100 100%
0% 0
AI
36 36%
64% 64

User comments

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Social recommendations and mentions

Based on our record, Evidently AI 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.

Evidently AI mentions (2)

  • [D] Using MLFlow for model performance tracking
    It is doable. However the main focus of MLFlow is in experiment tracking. I would suggest for you to look into another monitoring tools such evidentlyai . You can track more things than performance (e.g.data drift). Which may be helpful in a production setting. Source: almost 2 years ago
  • Five Data Quality Tools You Should Know
    Evidently is an open-source Python library that analyzes and monitors machine learning models. It generates interactive reports based on Panda DataFrames and CSV files for troubleshooting models and checking data integrity. These reports show model health, data drift, target drift, data integrity, feature analysis, and performance by segment. - Source: dev.to / over 2 years ago

What are some alternatives?

When comparing Spyne.ai and Evidently AI, you can also consider the following products

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.

ML Showcase - A curated collection of machine learning projects

PhotoAiD - Take passport photos where and when you want!

Censius.ai - Building the future of MLOps

ZapBG - Remove backgrounds fast & easily with just a few clicks.

iko.ai - Real-time collaborative notebooks on your own Kubernetes clusters to train, track, package, deploy, and monitor your machine learning models.